Posted on: 12/05/2026
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
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