Role Overview :

As a Senior Data Scientist, you will serve as a technical anchor within our analytics division, transforming complex, unstructured datasets into actionable business intelligence. Your day-to-day involves architecting end-to-end machine learning pipelines, conducting deep-dive statistical analyses, and deploying predictive models that directly influence product strategy.

You will collaborate closely with cross-functional teams, including product managers, data engineers, and executive stakeholders, to bridge the gap between technical innovation and commercial objectives. By delivering high-impact insights, you will play a pivotal role in optimizing customer experiences and driving data-backed decision-making across our metro-based operations.

Key Responsibilities :

- Develop and deploy scalable machine learning models to solve high-priority business problems, ensuring that solutions are robust, reproducible, and aligned with organizational goals.

- Architect sophisticated data pipelines and modeling frameworks that streamline the transition from raw data to production-ready insights for internal stakeholders.

- Translate complex analytical findings into intuitive data visualizations and executive-level presentations to influence strategic direction and operational efficiency.

- Mentor junior team members by conducting code reviews and sharing best practices in statistical modeling and software engineering to elevate the overall technical maturity of the team.

- Partner with data engineering teams to optimize data infrastructure and ensure the integrity, availability, and performance of large-scale datasets used for predictive analytics.

Required Skillset :

- Demonstrated expertise in Python and R for statistical analysis and model development, coupled with a strong command of SQL for complex data extraction and manipulation.

- Proven ability to design and implement deep learning architectures using frameworks like TensorFlow and PyTorch to solve challenging problems in Natural Language Processing and predictive modeling.

- Strong foundation in statistical inference and data modeling, with the ability to select the right mathematical approach for diverse business scenarios.

- Exceptional communication skills, with the ability to articulate technical concepts to non-technical stakeholders and foster collaboration across diverse, high-performing teams.

- A Master's degree or higher in a quantitative discipline such as Statistics, Mathematics, Computer Science, or Engineering from a premier institute with 4 to 9 years of work experience.

- High degree of adaptability and comfort working in a hybrid or on-site environment, demonstrating the ability to manage complex projects independently while maintaining alignment with team objectives.

- Proficiency in handling Big Data ecosystems and integrating data engineering best practices into the machine learning lifecycle to ensure seamless deployment and scalability.