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Data Scientist - Global Insurance Firm York | Manchester | Hybrid   Company Overview Our client is a global specialist insurer known for its innovative approach to risk and commitment to leveraging technology and data to drive better business decisions. With a strong presence in international markets, the organisation focuses on delivering high-quality insurance solutions while continually investing in advanced analytics, AI, and data capabilities.   The business promotes a collaborative, forward-thinking culture where data and technology play a central role in shaping strategy and delivering measurable value. Teams work across multiple functions to build impactful solutions that enhance underwriting, pricing, and operational decision-making.   Job Summary Our client is seeking a Data Scientist to join a growing analytics team supporting decision-making across the London Market. This is a high-impact role where you will act as a critical thinker and problem solver, applying advanced analytics and innovative thinking to complex business challenges.   You will work across multiple business areas, delivering both ad-hoc analysis and predictive or prescriptive models that support strategic and operational decisions. The role offers the opportunity to work with diverse datasets, apply modern machine learning techniques, and help strengthen the organisation’s data-driven culture.   As part of a multidisciplinary technical team, you will collaborate closely with data engineers, analysts, and business stakeholders to design and deliver scalable data solutions. This position is ideal for someone who enjoys turning complex data into actionable insights and communicating the business value of analytics.   Key Responsibilities Develop analytical solutions that support business decision-making using industry best practices and emerging data science methodologies. Work across the end-to-end data science lifecycle, from understanding business challenges to designing and implementing analytical models. Analyse both internal and external datasets to generate insights and predictive capabilities. Apply machine learning, statistical modelling, and advanced analytics techniques to solve complex business problems. Collaborate with cross-functional teams including data engineers, analysts, and business stakeholders such as pricing and underwriting teams. Communicate analytical findings clearly to non-technical stakeholders and demonstrate the value of data-driven solutions. Contribute to the development and maturity of analytics practices across the organisation. Support continuous improvement by exploring new analytical approaches and technologies.   Required Skills Degree in STEM (Science, Technology, Engineering, Mathematics) or a closely related discipline, or equivalent practical experience. Experience in data science, advanced analytics, or machine learning, or a strong interest in developing expertise in these areas. Strong understanding of statistics and quantitative analysis. Experience developing predictive or prescriptive models to generate business insights. Proficiency in programming languages such as Python, R, or SQL. Familiarity with version control systems, Agile methodologies, and modern development tools. Ability to work both independently and collaboratively within small teams. Strong written and verbal communication skills with the ability to present complex analytical findings clearly to stakeholders.   Preferred Skills Postgraduate degree in a relevant field such as Data Science, Statistics, or Machine Learning. Experience applying data science within financial services or insurance environments. Exposure to large language models, prompt engineering, or generative AI technologies. Experience working with cloud platforms such as Google Cloud Platform (GCP). Interest or experience in natural language processing (NLP) or computer vision. Knowledge of a wide range of machine learning techniques, from classical statistical models to deep learning methods. Understanding of software development best practices.   Benefits Competitive salary and performance-related incentives Pension contributions Generous annual leave allowance Flexible and hybrid working options Professional development and learning opportunities Collaborative and innovative working environment Opportunity to work on high-impact analytics projects within a global organisation   Equal Opportunity Statement SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.

Senior Product Owner York | Hybrid | Global Insurance Firm   Company Overview Our organisation is a leading international business with a strong focus on using data, analytics and AI to improve decision-making, accelerate growth and increase operational efficiency.   Our data function is transforming data maturity across the organisation, empowering colleagues through improved data fluency and supporting a culture built around informed, customer-focused decisions. Commercial focus, continuous improvement and product-led delivery are central to our approach.   You’ll join a collaborative, multidisciplinary data function working across Data Engineering, Data Product, Data Management, Data Visualisation and Data Science, with a shared focus on delivering sustainable, high-quality data products aligned to organisational strategy, governance and business priorities.   Job Summary We’re looking for an experienced Data Product Owner / Technical Delivery Manager to play a key role in turning business priorities into valuable, deliverable data products.   This is a senior product-delivery position that sits at the intersection of business needs and technical execution. You’ll own and manage a prioritised backlog, coordinate multidisciplinary delivery teams and ensure initiatives move effectively from discovery through to release and live service.   Working closely with the Data Product Manager, you’ll make informed decisions around scope, priorities and sequencing while balancing business value, delivery risk, technical sustainability and operational readiness. Your work will directly contribute to improving the organisation’s data and reporting capabilities and creating long-term value from its data estate.   Key Responsibilities Own a prioritised, delivery-ready backlog that balances measurable value, user needs, risk, urgency, technical dependencies, capacity and long-term product sustainability. Translate business problems into clearly defined epics and user stories, including appropriate context, acceptance criteria, dependencies and expected outcomes. Maintain traceability from initial requests through delivery, acceptance and the realisation of business value. Lead end-to-end delivery planning and coordination across multidisciplinary teams, managing milestones, capacity, dependencies, risks, issues, blockers and scope changes. Provide clear and timely progress updates and decision information to relevant stakeholders. Coordinate technical discovery, design assurance, testing and release-readiness activities, ensuring appropriate technical and operational considerations are addressed. Ensure architecture, security, data governance, non-functional requirements, operational controls and residual risks are appropriately considered throughout delivery. Connect business priorities with technical execution, facilitating effective decisions and constructive challenge across business and technology teams. Manage delivery partners and dependencies to maintain momentum and accountability. Support the transition of new capabilities into business-as-usual operations and promote effective, collaborative and continuously improving ways of working.   Qualifications & Skills Product & Delivery Proven experience as a Product Owner, Technical Product Owner, Delivery Manager or in a comparable product-delivery role. Strong experience of backlog management, including writing effective user stories and acceptance criteria. Strong understanding of Agile delivery, estimation, planning, dependency management, risk management, testing, release readiness and transition into live service. Working knowledge of architecture, integrations, environments, security, data governance and non-functional requirements. Sufficient technical credibility to identify constraints, challenge assumptions and explain delivery trade-offs effectively.   Professional Skills Strong judgement and an outcome-focused approach, with the ability to make clear decisions around scope, priority and sequencing. Excellent communication, facilitation and stakeholder-management skills across business, technical and senior audiences. Confidence to constructively challenge, influence stakeholders and manage competing priorities. Highly organised and accountable, with the ability to lead complex delivery through ambiguity. Strong problem-solving skills and the ability to remove blockers while maintaining delivery momentum and quality. A continuous-improvement mindset and a collaborative approach to working across organisational boundaries.   Experience Demonstrable experience leading product delivery within a complex organisation, with accountability for backlog management, planning and end-to-end coordination from discovery through release and support. A track record of influencing across organisational boundaries and resolving complex dependencies. Experience balancing business value, delivery risk, technical sustainability and operational readiness.   Preferred Relevant accreditation in Product Ownership, Scrum, Agile delivery, project delivery or a similar discipline. Experience using Jira, Confluence or comparable collaboration and documentation tools. Knowledge of data platforms, reporting and analytics products. Understanding of data governance and data quality principles. Experience of supplier management or business-as-usual product operations.   Benefits We believe that a diverse and inclusive workforce creates stronger teams and better outcomes. We’re committed to creating an environment where people can do their best work while maintaining a healthy balance between professional and personal life.   Our hybrid working approach provides a balance of collaboration, structure and social interaction alongside the independence and flexibility of working remotely.   Performance-related bonus. Contributory pension. 25 days' annual leave, plus additional company days. A four-week paid sabbatical after every five years of service. Private medical cover for employees and their families. Opportunities for professional development and continuous learning. A flexible, collaborative and inclusive working environment. The opportunity to work on high-impact data, analytics and technology initiatives within a complex international organisation.   Equal Opportunity Statement We are an equal opportunities employer and are committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.   If this is of interest, please feel free to reach out using the details below.   jarret.devlin@spgresourcing.com 01617110288

Forward Deployed Scientist - Pharma Location: Hybrid, regular on-site in Oxford, UK Level: Senior / Principal The role We build AI systems that accelerate complex generics and 505(b)(2) formulation work, plus a causal engine that predicts what happens when you change a formulation, targeting PK and bioequivalence. It's a concierge model: clients never touch the platform, our scientists do. You own the client relationship, run real discovery, judge whether our output is actually useful, and turn field constraints into requirements engineers can build. What you'll do Own the client relationship. Find out what's been tried, what failed, what's frozen, what the process can really do, and what decision they need to make. Half the job is discovery, before any analysis starts. Gatekeep quality. Every deliverable goes through you first. Is it implementable at scale? Does it answer the real question? You can kill work before it ships. Push past the obvious. If the output reads like a literature review, send it back. Force the causal engine and the client's own data to actually earn their keep. Turn constraints into product requirements. "This process can't hit half a percent error" isn't small talk, it's a spec. Write it up so engineering can build against it. Bridge both sides. Technical enough to challenge the engineering team, credible enough that a client's development lead treats you as a peer. Compound every engagement. Log what was asked, what we found, what the data couldn't answer, and what the client valued. That becomes the evidence base. Who you are An industrial formulation / CMC scientist who has shipped real dosage forms and sat through a failed study. Core experience PhD in pharmaceutics, pharma sciences, chemical engineering (or a Master's with more industry time) 5+ years in generics, complex generics, or 505(b)(2) Hands-on with solid oral dosage forms: modified/extended release, coating, dissolution methods, scale-up You've had a BE study fail, diagnosed why, and fixed it. Worth more than any credential You know what a plant can and can't reliably do: batch variability, yield loss, where lab-scale ideas break Fluent in FDA guidance, IID limits, ICH stability, PK endpoints, BE stats You read the data yourself and you'll get fluent in our stack. No need to code AI fluency You already use AI tools daily, literature, data, protocols, reasoning, and have a real opinion on where they help and where they don't You've been burned by a confident wrong answer in your own field, and you can tell the story. That earned scepticism matters more than enthusiasm You interrogate AI output instead of accepting it When a tool falls short, your instinct is to fix it, not just complain Also required You find the constraint everyone else assumed away Generalist range: mechanism, stats, process, regulatory, without handing off to a specialist each time You can tell a development lead their approach is broken and they'll thank you for it Intellectual honesty: "this data can't answer that, here's the experiment that would," beats a confident answer that fits the slide Comfortable with ambiguity, five people, no playbook, real deadlines

Data Scientist  Location: Leeds (Hybrid) Salary: Up to £65,000 Role Purpose The Data Scientist supports data-driven decision making by developing statistical, machine learning, and advanced modelling solutions across structured and unstructured data. They want a Data Scientist who develops and deploys predictive models, advanced algorithms, and data products that identify patterns, forecast outcomes, and generate deeper insights to support strategic and business initiatives. Accountabilities and Responsibilities: •    Identify high-impact business use cases and design appropriate statistical or machine learning solutions. •    Build, validate, optimise, and deploy analytical and predictive models, including classification, regression, clustering, time-series analysis, and anomaly detection. •    Curate, prepare, and manage structured and unstructured datasets using appropriate data storage and processing approaches. •    Develop dashboards and visualisations where required to communicate analytical findings and model outputs effectively. •    Ensure data quality and integrity and contribute to relevant data governance practices. •    Collaborate with business and technical stakeholders to translate complex analytical outputs into clear, actionable recommendations. •    Identify opportunities for algorithmic optimisation, automation, and the application of emerging data science techniques. •    Contribute to the development and continuous improvement of data products, analytical methodologies, and modelling practices. •    The role has a distinct focus on advanced analytical and predictive solutions, differentiating it from Data Analyst positions that primarily focus on reporting, data exploration, business intelligence, and operational analytics. Knowledge, Experience & Technical Know-How: •    Strong analytical, statistical, mathematical, and problem-solving skills. •    Practical experience applying machine learning techniques and managing the model development lifecycle. •    Proficiency in SQL and data visualisation tools such as Power BI, Tableau, or equivalent platforms. •    Experience working with structured and unstructured data, cloud-based technologies, and scalable data processing environments. •    Ability to communicate complex statistical and modelling concepts clearly to non-technical audiences. •    Familiarity with enterprise business systems and cloud environments is desirable. •    Experience using Python, R, or other programming and statistical languages commonly used in data science. •    Understanding of data quality, governance, and responsible use of analytical models. •    Experience selecting appropriate modelling approaches and evaluating model performance against defined business objectives. •    These capabilities distinguish the Data Scientist role from Data Analyst positions, which generally have a stronger emphasis on data exploration, reporting, visualisation, and business intelligence. •    Professional experience in data science, statistical modelling, machine learning, predictive analytics, or a related field. •    Demonstrable experience developing analytical or predictive solutions that support business decision making. Equal Opportunity Statement SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.  

Machine Learning Engineer Location: Flexible (Hybrid) Working set up: Hybrid Salary: Competitive + bonus + benefits   SPG are working on behalf of an established financial services organisation investing heavily in its data science and AI capabilities. As part of an expanding team, the business is delivering a range of greenfield machine learning and generative AI initiatives designed to solve real-world business challenges and enhance customer outcomes. This is an exciting opportunity to join a collaborative data function where you'll help shape the organisation's machine learning engineering capability while building scalable, production-ready AI solutions.   The Role Working as part of a cross-functional Data Science team, the Machine Learning Engineer will play a key role in taking machine learning models from research through to production. You'll work closely with Data Scientists, Data Engineers and Software Engineers to build robust, scalable ML solutions while helping define best practices, tooling and automation across the full machine learning lifecycle. This role is ideal for someone with a passion for software engineering, cloud technologies and productionising machine learning solutions within an enterprise environment.   Key responsibilities Design, develop and enhance the organisation's machine learning engineering capability and Data Science platform Build and automate end-to-end machine learning workflows using CI/CD and Infrastructure as Code Collaborate with Data Scientists throughout the model development and deployment lifecycle Work closely with engineering teams and business stakeholders to deliver production-ready AI solutions Develop high-quality, maintainable Python code following software engineering best practices Contribute to technical design decisions including model deployment strategies and solution architecture Support the deployment and operationalisation of both traditional machine learning and Generative AI solutions Help establish engineering standards, tooling and best practices as the function continues to grow   Required skills and experience Commercial experience in Machine Learning Engineering or Data Science within a production environment Strong Python development skills with a solid understanding of software engineering best practices Experience deploying machine learning solutions into cloud-native production environments Experience with containerisation technologies such as Docker and orchestration platforms including Kubernetes Knowledge of modern MLOps practices including CI/CD, version control (Git) and infrastructure automation Experience working with cloud platforms and modern data ecosystems (Azure and Databricks experience beneficial) Strong understanding of machine learning principles and model deployment processes Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders Experience working with Agile delivery methodologies and tools such as Azure DevOps and Jira   Desirable experience Experience working with Large Language Models (LLMs), Generative AI or Agentic AI solutions in a commercial environment Experience deploying machine learning models within regulated industries such as financial services or insurance Exposure to enterprise-scale MLOps and cloud infrastructure Experience contributing to platform architecture and engineering best practices

Delivery Consultant Location: Leeds Desk: Data or Change & Transformation or Software   As we continue to grow, we’re looking for an ambitious, driven Delivery Consultant to join the team.   This is a genuine opportunity for someone who thrives in a fast-paced environment, enjoys building strong relationships, and wants to play a key role in delivering top talent across the tech market. If you’ve got experience in recruitment delivery, candidate management, and you’re ready for your next step we’d love to speak.   About SPG Resourcing We’re a specialist technology recruitment partner working with organisations delivering real, business-critical technology change across the UK. We focus on Data, Change & Transformation, and Software partnering with clients where hiring genuinely matters. No volume. No churn.   With a strong foundation already in Leeds, we’re now hiring experienced Delivery Consultant who want autonomy, ownership and the backing to build a desk properly.   The Opportunity You’ll focus on the delivery side of the recruitment process: identifying, engaging and managing high-quality candidates across your specialist market.   Sourcing and engaging top tech talent Managing candidates through the full recruitment process Building strong candidate relationships and networks Working closely with consultants to deliver on live roles Ensuring a high-quality candidate experience   About You Experience in recruitment delivery, resourcing or candidate management (at least 2 years+) Ideally exposure to the tech market (not essential) Strong communication and relationship-building skills Organised, proactive and able to manage multiple roles Driven, ambitious and keen to develop your career Able to commute to Leeds office   Why Us Our MD stays close to the action not sat on the sidelines, but present in the business, active in the market. He knows exactly what it takes to win and build a desk today, because he chooses to, not because he has to!   You won’t be managed from a distance you’ll be working directly with someone who understands the reality of the market, adds value and leads from the front.   It’s a big part of why people join and stay leadership is visible, accessible and genuinely invested in your success. If you want to grow, you’ll be supported to do it properly, with clear progression and real opportunities as the business scales.   We’re building this with intent: Quality over headcount: we hire carefully and invest in people for the long term High standards, always: performance matters and we don’t dilute that Substance over noise: relationships, credibility and delivery come first Real investment in you: clear progression, proper support and the space to build something meaningful   You’ll be part of a high-performing, collaborative, straight-talking environment where expectations are clear and standards are high without the noise.   What You’ll Get Uncapped earning potential: competitive base + uncapped commission + performance rewards Strong benefits package: private medical (incl. dental & optical), wellbeing support, pension Clear career progression: structured development and promotion based on performance A proper working environment: collaborative, high-performing, built on trust Flexibility that works: hybrid model + birthday leave + Christmas shutdown   Additional Benefits £2,000 annual training & development budget 25 days holiday + bank holidays Enhanced family-friendly policies maternity, paternity, sick etc) Incentives: lunch clubs, trips away, team building days long term service benefits etc   How to Apply Send your CV to hr@spgresourcing.com or reach out to our Head of HR & Operations Kinga Liu for an informal chat.   Equal Opportunities SPG Resourcing is an equal opportunities employer committed to creating an inclusive workplace. We provide reasonable adjustments throughout the recruitment process where required.   *Please note, we are unable to offer visa sponsorship for this role.

Senior / Principal Technology Recruiter Location: Manchester Desk: Data or Change & Transformation or Software   Build your desk. Shape your market. Be part of something that’s actually going somewhere.     About SPG Resourcing We’re a specialist technology recruitment partner working with organisations delivering real, business-critical technology change across the UK. We focus on Data, Change & Transformation, and Software partnering with clients where hiring genuinely matters. No volume. No churn.   With a strong foundation already in Manchester, we’re now hiring experienced recruiters who want autonomy, ownership and the backing to build a desk properly.   The Opportunity You’ll run your desk like a business owning your market, building relationships and delivering consistent billings through quality.   Build and win new business within your vertical Develop strong, credible client and candidate relationships Own and grow your specialist market Manage your pipeline, forecasting and desk performance Deliver high-value, high-quality placements   About You 4+ years’ experience in 360 UK Tech recruitment Strong billing or consistent performance track record Commercial, relationship-led approach Able to commute to Manchester (3 days per week)   Why Us Our MD stays close to the action not sat on the sidelines, but present in the business, active in the market. He knows exactly what it takes to win and build a desk today, because he chooses to, not because he has to!   You won’t be managed from a distance you’ll be working directly with someone who understands the reality of the market, adds value and leads from the front.   It’s a big part of why people join and stay leadership is visible, accessible and genuinely invested in your success. If you want to grow, you’ll be supported to do it properly, with clear progression and real opportunities as the business scales.   We’re building this with intent: Quality over headcount: we hire carefully and invest in people for the long term High standards, always: performance matters and we don’t dilute that Substance over noise: relationships, credibility and delivery come first Real investment in you: clear progression, proper support and the space to build something meaningful   You’ll be part of a high-performing, collaborative, straight-talking environment where expectations are clear and standards are high without the noise.   What You’ll Get Uncapped earning potential: competitive base + uncapped commission + performance rewards Strong benefits package: private medical (incl. dental & optical), wellbeing support, pension Clear career progression: structured development and promotion based on performance A proper working environment: collaborative, high-performing, built on trust Flexibility that works: hybrid model + birthday leave + Christmas shutdown   Additional Benefits £2,000 annual training & development budget 25 days holiday + bank holidays Enhanced family-friendly policies maternity, paternity, sick etc) Incentives: lunch clubs, trips away, team building days long term service benefits etc   How to Apply Send your CV to hr@spgresourcing.com or reach out to our Head of HR & Operations Kinga Liu for an informal chat.   Equal Opportunities SPG Resourcing is an equal opportunities employer committed to creating an inclusive workplace. We provide reasonable adjustments throughout the recruitment process where required.   *Please note, we are unable to offer visa sponsorship for this role.

Lead Machine Learning Engineer - Global Insurance Firm London | Hybrid   Company Overview Our client is a global organisation operating within the insurance and financial services sector, recognised for its commitment to innovation and the strategic use of data and technology. The business is investing heavily in modern data platforms, artificial intelligence, and advanced analytics to drive smarter decision-making and deliver value across its operations.   With a strong focus on collaboration and continuous improvement, the organisation brings together multidisciplinary teams spanning data science, engineering, and technology to build scalable, production-grade solutions. Employees are encouraged to contribute new ideas, develop their technical capabilities, and play an active role in shaping the organisation’s data-driven future.   Job Summary Our client is seeking a Lead Machine Learning Engineer to shape and scale its machine learning engineering capability while ensuring the successful deployment and operation of machine learning solutions in production environments.   This leadership role combines technical expertise with people management responsibilities, overseeing a team of Machine Learning Engineers while driving best practices across machine learning deployment, infrastructure, and MLOps. You will play a critical role in building scalable platforms, establishing engineering standards, and enabling teams to deliver robust, production-ready machine learning systems.   Working closely with data science teams, platform engineers, and senior stakeholders, you will ensure the organisation can efficiently move machine learning models from experimentation to reliable production systems. This role offers the opportunity to influence technical strategy, mentor engineers, and contribute to the development of enterprise-scale machine learning capabilities.   Key Responsibilities People Leadership Manage and develop Machine Learning Engineers, including setting objectives, conducting performance reviews, and supporting career progression. Foster a strong engineering culture that emphasises collaboration, quality, and operational excellence. Provide mentorship and coaching to support both technical and professional development.   Strategic Capability Development Define and evolve machine learning engineering strategy in alignment with organisational objectives. Establish engineering standards for machine learning deployment, infrastructure, and operational practices. Drive capability development across teams, including upskilling in MLOps, cloud platforms, and software engineering best practices.   Technical Enablement & Platform Ownership Lead the ownership and evolution of the organisation’s MLOps platform, ensuring reliability, scalability, and security. Enable scalable and reusable machine learning delivery across multiple business initiatives. Lead technical exploration activities such as proof-of-concepts and architectural investigations.   Governance & Standards Ensure machine learning systems comply with security, architecture, and operational standards. Establish guardrails for production machine learning systems, including monitoring, retraining, deployment, and lifecycle management.   Collaboration & Influence Partner closely with data science teams to ensure effective transition from experimentation to production deployment. Collaborate with platform and engineering teams to integrate machine learning solutions into enterprise systems. Represent machine learning engineering within strategic technology discussions and influence platform and tooling decisions.   Qualifications and Skills Required Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or another quantitative discipline, or equivalent practical experience. Significant experience as a Senior or Lead Machine Learning Engineer delivering machine learning systems in production environments. Strong understanding of machine learning and data science concepts, including supervised and unsupervised learning, feature engineering, and model evaluation techniques. Demonstrated experience leading or mentoring engineering teams, setting standards, and developing technical capabilities. Proven experience owning or managing MLOps platforms or critical machine learning infrastructure. Experience designing and implementing frameworks to evaluate the commercial impact of machine learning systems in production. Experience collaborating with data scientists throughout the end-to-end machine learning lifecycle. Strong communication skills and ability to work within Agile, cross-functional teams.   Preferred Experience working within insurance, financial services, or other regulated industries. Experience implementing enterprise-scale machine learning platforms and governance frameworks. Exposure to advanced monitoring, incident management, and reliability practices for machine learning services.   Key Technical Skills Python within a machine learning engineering context, including object-oriented programming, testing, and design patterns Experience deploying, monitoring, and maintaining machine learning models in production systems Cloud platforms such as AWS, Azure, or Google Cloud Containerised deployments using Docker or similar technologies MLOps practices, including CI/CD pipelines and Git-based development workflows Infrastructure as Code tools such as Terraform Experience with API operations, monitoring, logging, and reliability management Strong working knowledge of SQL and data integration across application ecosystems   Benefits Competitive salary and performance-based incentives Pension contributions Generous annual leave allowance Flexible and hybrid working arrangements Professional development and leadership growth opportunities Collaborative and innovative technical environment Opportunity to shape enterprise-scale machine learning engineering capabilities   Equal Opportunity Statement SPG Resourcing is an equal opportunities employer and is committed to fostering an inclusive workplace which values and benefits from the diversity of the workforce we hire. We offer reasonable accommodation at every stage of the application and interview process.