Staff / VP, Data Scientist (UK)

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees.

We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development.

You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation.

At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses.

The Role

As the Staff Data Scientist (VP) on the AI Science team, you will be responsible for designing and leading high-impact data science initiatives that drive business value across the enterprise. Reporting to the Executive Director of AI Science, you will play a critical role in shaping data-driven strategy, developing advanced statistical and machine learning models, and delivering insights that inform decision-making, optimize operations, and uncover new growth opportunities. You will act as both a technical thought leader and a strategic partner, fostering a culture of rigorous experimentation, reproducibility, and responsible AI adoption while mentoring the next generation of data scientists.

Key Responsibilities:

• Lead the design and execution of data science projects that solve complex business problems across critical workflows.
• Develop and apply advanced AI/ML methods including statistical modeling, causal inference, forecasting, optimization, and machine learning.
• Partner with stakeholders to translate business challenges into analytical frameworks, ensuring results are actionable and aligned with strategic priorities.
• Drive the adoption of emerging analytical techniques and tools (e.g., generative AI, LLM-based analytics, simulation modeling, RAG for knowledge discovery).
• Collaborate with ML engineers to scale prototypes into production-ready systems, ensuring reliability, fairness, and generalizability.
• Design and maintain metrics and experiments (A/B testing, uplift modeling, KPI design) to measure model and business impact.
• Communicate findings through compelling data storytelling, dashboards, and executive-level presentations.
• Provide thought leadership in responsible AI practices, ensuring transparency, fairness, and compliance with internal governance and external regulations.
• Mentor and guide other data scientists, fostering technical excellence, innovation, and collaboration across the team.

Requirements

Qualifications:

• 8+ years of experience in data science or applied statistics roles, with a proven track record of driving measurable business impact.
• Expertise in one or more of supervised and unsupervised machine learning, deep learning, time series analysis, causal inference, and statistical modeling.
• Experience leading end-to-end data science projects from ideation to delivery, including business scoping and stakeholder management.
• Strong proficiency in Python (or R), with deep experience using modern data science libraries (e.g., Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Statsmodels).
• Solid foundation in SQL and data wrangling across large, complex datasets.
• Hands-on experience with experimentation platforms, data visualization, and dashboarding tools (e.g., Tableau, Power BI, Plotly).
• Familiarity with cloud-based data platforms (AWS, GCP, Azure) and collaborative tools (Databricks, Snowflake) is a plus.
• Exceptional ability to translate technical results into clear, actionable insights for senior executives and non-technical audiences.
• Master's or PhD in Statistics, Data Science, Computer Science, Economics, or a closely related discipline.

Preferred Qualifications:

• Experience working with Palantir platforms (Foundry, AIP, Ontology) to develop, analyze, and operationalize data-driven insights within enterprise-scale environments.
• PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline. Publications in top-tier AI/ML or data science conferences or journals (e.g., NeurIPS, ICML, KDD, AAAI, ACL, JASA).
• Recognized contributions to the open-source data science / ML ecosystem (e.g., libraries, frameworks, toolkits, widely adopted notebooks).
• Track record of thought leadership through invited talks, keynote presentations, or leadership roles in professional societies, conferences, or meetups.
• Experience mentoring teams at scale and establishing standards for reproducibility, experimentation, and responsible AI.
• Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics.
• Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer) are a plus.

Benefits

• Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services.
• Drive AI transformation for some of the most sophisticated financial entities.
• Competitive compensation, benefits, future equity options, and leadership opportunities.
  

Position Location

This is a hybrid position based in the United Kingdom.

Compensation

We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits.

TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.