Decision Science Analyst - Finance

You will leverage SQL, Python, and advanced statistical and machine learning methods to automate processes, build predictive models, and deliver data-driven insights that influence decision making. You will partner closely with cross-functional stakeholders including IT, lead experimentation and model evaluation, and turn complex data into meaningful business impact. ROLE AND RESPONSIBILITIES: Translate finance and business needs into well-defined decision science problems by framing hypotheses, success metrics, and evaluation approaches; communicate progress and outcomes clearly to stakeholders Partner closely with Finance stakeholders, product teams, and IT data engineering and data science to drive adoption of high-impact, production-grade analytical solutions Design, develop, and evaluate predictive and statistical solutions that improve financial planning, forecasting, and decision-making across the enterprise. Champion analytical rigor and structured problem-solving through clear storytelling, stakeholder workshops, and thoughtful articulation of insights, risks, and trade-offs Classical ML models (classification, regression, forecasting, clustering), feature pipelines, and explainability (e.g., SHAP RAG pipelines and vector search for knowledge use cases Implement production-ready Python code with high-quality engineering standards: Git-based workflows, code reviews, automated tests, documentation, and reproducibility. Bring various elements of demand and supply vectors ( Market, Commodity prices, Weather, historical data, Product competition, Supply side dynamics, AI prices) into financial models Provide an outside in view of Financial forecasting using various data and decision science modelling to challenge and provide a reference for traditional financial forecasting process. WHO YOU ARE: Master s degree with 3+ years of experience in decision science, data science, or advanced analytics delivering production-grade solutions Strong foundation in statistical modeling, machine learning, and forecasting, with experience evaluating model performance and business impact. Ability to develop financial acumen, understand financial statements and planning processes, and apply advanced analytics to finance use cases. Experience working with modern data platforms and scalable analytical environments. Proven problem-solving skills in ambiguous settings, with a track record of turning complex data into actionable insights. Effective communicator who can translate technical results into clear business implications for Finance stakeholders. Commitment to high-quality engineering practices, documentation, and responsible data use. Fluent in English (written and spoken); additional languages are a plus Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.