Senior Data Scientist (AI/ML)

Description : Responsibilities & Key Deliverables :Quantitative Modeling & Strategy :- Architect, develop, and validate sophisticated statistical and econometric models to drive predictive forecasting, assess risk, and inform critical business strategy.- Own the entire modeling lifecycle, from hypothesis generation and data discovery through to production deployment, monitoring, and iterative improvement.Machine Learning & AI Solution Architecture :- Lead the end-to-end design and implementation of scalable machine learning solutions to solve complex business challenges, applying advanced techniques in areas like NLP, deep learning, or time-series analysis.- Establish and champion MLOps best practices to ensure the robustness, scalability, and maintainability of our AI/ML systems.Strategic Analysis & Insight Generation :- Translate ambiguous, high-level business questions into concrete analytical frameworks and quantitative research plans.- Conduct deep-dive exploratory analyses to uncover novel insights, identify strategic opportunities, and quantify potential business impact.Stakeholder Partnership & Influence :- Act as a strategic partner and quantitative advisor to senior leadership and cross-functional teams (e.g., Product, Finance, Marketing).- Influence the direction of key business initiatives by translating complex analytical results into clear, actionable recommendations.Executive Communication & Data Storytelling :- Develop and present compelling data narratives and visualizations to communicate complex quantitative concepts and findings to executive and non-technical audiences.- Design and oversee strategic dashboards and reporting frameworks that provide a clear, accurate view of business performance and model outcomes. Data Governance & Quality Assurance :- Define and enforce data quality frameworks and validation strategies for critical datasets used in modeling and analysis.- Collaborate with data engineering to architect and optimize data pipelines, ensuring the integrity and accessibility of data for the entire analytics organization.- Demonstrated expertise in leading the full lifecycle of data-driven projects, from formulating ambiguous questions to deploying models and measuring their financial or operational impact.- Extensive experience architecting solutions for large-scale, complex datasets and applying advanced analytical techniques to drive strategic outcomes.Experience : - 6-10 years of professional experience in quantitative finance, data science, econometrics, or a similar advanced analytical field.Industry Preferred : Manufacturing - Preferably Auto & Ancillary Business (ref:hirist.tech)