Digital Finance Analytics – Data Science & GenAI Lead

Thermo Fisher Scientific • Carlsbad, CA

1d • Hybrid

About The Position

We are seeking a highly motivated Digital Finance Analytics DS/AI Lead to drive advanced analytics and Generative AI solutions that improve business insights, financial planning, forecasting, and decision support. This role sits within Finance and partners closely with FP&A, Business Unit Finance, Pricing, Commercial, Operations, and Marketing teams (as well as Strategy) to translate business questions into scalable analytical products—delivering forecast accuracy, scenario insights, profitability drivers, performance attribution, and executive-ready storytelling. The ideal candidate blends strong finance acumen with hands-on analytics skills (SQL/Python) and experience applying machine learning/GenAI techniques to automate analysis and enhance insight generation. This is a high-impact role requiring stakeholder leadership, structured problem solving, and the ability to communicate complex findings clearly to senior leadership. This is a hybrid position in Carlsbad, CA.

Requirements

• Bachelor’s degree required in a quantitative discipline (Finance, Economics, Statistics, Analytics, Data Science, or related); Master’s preferred.
• 5+ years experience in Finance, FP&A, or Finance Analytics with demonstrated advanced analytics/modeling experience.
• Proven track record partnering with senior stakeholders and delivering analytics that impacts financial outcomes.
• Strong finance fundamentals (forecasting, budgeting, variance analysis, profitability drivers, KPIs).
• Advanced analytical capability: SQL/Python, statistical analysis, modeling, and data visualization.
• Experience applying ML techniques to business problems; ability to evaluate models using practical metrics and explain results.
• Familiarity with GenAI concepts and responsible use in business workflows (prompting, evaluation, governance considerations).
• Excellent communication skills and ability to influence in a matrixed environment; comfortable translating ambiguity into structured deliverables.

Nice To Haves

• Spark a plus
• ML/AI: scikit-learn; exposure to GenAI/LLM tooling (e.g., OpenAI/LLM SDKs, LangChain/LangGraph)

Responsibilities

• Lead the development of analytics solutions supporting FP&A forecasting, scenario planning, profitability and cost drivers, performance attribution, and business decision support.
• Partner with Finance stakeholders to define problems, align success metrics, and deliver insights that influence investment, resource allocation, and operating decisions.
• Create executive-ready narratives, visuals, and recommendations—connecting analytics outputs to business outcomes.
• Build and validate predictive models and analytical frameworks (e.g., forecasting models, driver-based models, segmentation, anomaly detection).
• Develop and apply GenAI/NLP solutions to accelerate finance workflows (e.g., automated variance commentary, summarization of financial drivers, search/Q&A over finance documentation and reporting content).
• Establish model performance standards (backtesting, accuracy/error metrics, stability monitoring) and ensure results are interpretable and decision-relevant.
• Design curated datasets and repeatable pipelines that integrate finance and operational data for analysis (actuals, forecast, budget, drivers, and relevant external signals).
• Improve reporting efficiency through automation and reusable analytical components, enabling self-service insights and consistent definitions.
• Ensure data quality, documentation, lineage, and governance aligned to Finance expectations (controls, auditability, repeatability).
• Collaborate with Pricing to quantify price realization, elasticity and trade-offs, and evaluate pricing actions that improve margin outcomes.
• Partner with Commercial teams to understand pipeline and demand drivers, segment/customer performance, and growth opportunities tied to leading indicators.
• Work with Operations and Supply Chain to model cost-to-serve, productivity, inventory/working capital drivers, and operational scenarios.
• Coordinate with Marketing to measure campaign effectiveness, funnel conversion, and ROI impact on revenue and forecast drivers.
• Collaborate with data engineering/platform teams to productionize analytics where needed, ensuring reliability, controls, and appropriate monitoring.
• Contribute to best practices, templates, and playbooks for finance analytics and GenAI usage; support upskilling through documentation, office hours, and knowledge sharing.

Benefits

• A choice of national medical and dental plans, and a national vision plan, including health incentive programs
• Employee assistance and family support programs, including commuter benefits and tuition reimbursement
• At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
• Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level