Senior Quantitative Analyst - Automotive

Description:

Employer : Leading Automotive Co.

Role : Quantitative Analyst

Designation : Senior Quantitative Analyst

Job Location : Mumbai(Kandivli/ Sewri)

Job Description:

Objective:

The Senior Quantitative Analyst serves as a critical partner to leadership, translating complex data into robust, quantitative strategies that yield a measurable competitive advantage. This position is essential for powering data-driven strategy, optimizing performance, and ensuring analytical rigor across the organization's most important initiatives.

Roles and Responsibilities:

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.

Primary Skills:

Core Technical Competencies:

Programming & ML Systems:

- Expert-level command of Python and its scientific computing stack (e.g., Pandas, NumPy, Scikit-learn).

- Deep, hands-on experience applying major ML/Deep Learning frameworks (e.g., TensorFlow, PyTorch) to build and deploy models in a production cloud environment.

- Practical knowledge of MLOps principles and tools (e.g., MLflow, Kubeflow, Airflow) for creating automated and scalable ML pipelines.

Quantitative & Statistical Modeling:

- Deep theoretical and applied mastery of advanced statistical methods, including econometric modeling, time-series analysis, Bayesian methods, and experimental design (A/B testing).

- Proven ability to select, develop, and validate the appropriate modeling technique for complex and ambiguous business problems.

Data Warehousing & Big Data Platforms:

- Expert-level proficiency in SQL for complex querying, data manipulation, and performance tuning.

- Extensive experience with modern cloud data warehouses (e.g., Google BigQuery, Snowflake, AWS Redshift) and hands-on experience with big data technologies (e.g., Spark, Dask).

Data Storytelling & Executive Communication:

- Mastery of data visualization techniques to create compelling narratives that communicate complex analytical results to senior leadership and non-technical stakeholders. Proficiency with tools like Tableau, Looker, or programmatic libraries is expected.