Data Scientist – Generative AI Full Time NEW

About Synechron:

Synechron is a leading digital transformation consulting firm dedicated to delivering innovative technology solutions within banking, financial services, and insurance. We thrive on engineering excellence, collaboration, and a passion for cutting-edge technologies.

About role:

This role is to provide deep data science expertise across Generative AI, AI-enabled tools, and applied analytics, helping to build stronger evidence base for how AI capabilities are adopted, governed, and improved across engineering and adjacent workflows.

The successful candidate will build robust analytical approaches that help to understand where tools such as GitHub Copilot, Claude, and similar AI assistants deliver the strongest benefit, where outcomes are mixed, and what technical, workflow, behavioural, or organisational patterns explain those differences.

The purpose is not only to assess the impact and usage patterns of GenAI tools, but also to create practical insight that can be used by delivery leaders, enablement teams, and engineering communities to improve adoption quality, reinforce strong practices, and guide future AI-tool strategy.

This role will connect data science, AI-tool evaluation, engineering metrics, and GenAI adoption strategy. The output should enable better training, education, coaching, and knowledge transfer across the organisation, while helping to set a high internal standard for evidence-based adoption of AI tools in software engineering.

Job Location: Sheffield (Hybrid – 3 days in the office)

Responsible For:

• Developing the analytical roadmap for Generative AI and AI-tool insight across engineering and adjacent workflows
• Defining a robust data science strategy for evaluating the impact, adoption, value, and risks of Generative AI and AI tools across engineering workflows
• Building analytical frameworks to assess tools such as GitHub Copilot, Claude, and similar AI assistants across use cases, engineering workflows, and technical patterns
• Identifying where GenAI and AI tools are most influential across coding, knowledge work, engineering workflows, SDLC flow, deployment, and DORA-style measures
• Identifying the key adoption drivers, accelerators, blockers, and best practices associated with stronger productivity outcomes
• Working with programme leadership to translate analytical findings into actionable recommendations for engineering teams and stakeholders
• Collaborating with data scientists, engineers, product owners, and programme managers to refine models, hypotheses, and measurement methods
• Supporting the operationalisation of repeatable insight products, dashboards, and evidence packs that can be used at programme and leadership level
• Contributing to knowledge acquisition and knowledge transfer by helping convert findings into enablement actions, guidance, playbooks, and learning interventions
• Communicating findings clearly to senior stakeholders, including both technical and non-technical audiences

Major Challenges:

• This is a high-visibility initiative in a fast-moving area where expectations are high and the evidence needs to be both rigorous and practical
• Measuring the impact of Generative AI in engineering is analytically difficult because outcomes are influenced by team context, engineering maturity, task type, developer experience, and workflow differences
• The role requires balancing scientific robustness with the need to deliver useful, timely insight into a fast-evolving tool landscape
• The successful candidate must work comfortably across ambiguity, changing hypotheses, evolving adoption patterns, and imperfect real-world enterprise data
• This is an outcomes-driven role and will suit someone who is comfortable iterating quickly, challenging assumptions, and turning analysis into action across a fast-evolving AI landscape

ESSENTIAL CANDIDATE REQUIREMENTS (Experience, skills, competencies etc.)

• Self-starter.
• Track-record of developing knowledge acquisition, knowledge transfer, communities of interest processes and content.
• Proven ability to deliver globally across matrix-based organizations.
• Strong Influential communication and interpersonal skills, able to operate well across cultures and in multicultural, diverse work environment.
• Proficiency in verbal and written English, especially proficient in email communication, ppts, and in occasionally rewriting English content when written by a non-native speaker.
• Willing to learn, explore and implement new and emerging technologies.
• Ability to work in a fast-paced dynamic environment to deliver high quality results under tight schedule and pressure
• Proven experience in data analysis, particular in software development context
• Strong understanding of SDLD, Deployment and DORA metrics and their relevance to developer productivity
• Experience in translating data analysis into actionable business or operational insights
• Familiarity with GenAI technologies, specifically coding assistant like GitHub Copilot

Diversity Statement

Synechron are proud to be an equal opportunity employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We offer flexible workplace arrangements, mentoring, internal mobility, learning and development programmes to support our global workforce. Empowerment and collaboration are at the core of how we operate.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.