The Data Scientist will lead the design, deployment, and lifecycle management of AI initiatives, translating business needs into scalable data-driven solutions.

The role ensures data quality, optimized workflows, and measurable business impact through structured execution and continuous improvement.

In addition to delivering high-performance models, the position involves collaborating with stakeholders, aligning AI solutions with strategic objectives, and mentoring junior team members.

The role also drives long-term adoption through reusable frameworks and successful Build-Operate-Transfer (BOT) of AI solutions.

Responsibilities:

- Apply advanced ML techniques (ANN, XGBoost, Deep Learning, etc.) to solve complex business problems.

- Use state-of-the-art AI frameworks to improve accuracy, efficiency, and scalability.

- Optimize models via feature engineering, hyperparameter tuning, and algorithm selection.

- Manage the full AI lifecycle: data preparation, model building, deployment, and monitoring.

- Collaborate with engineering teams for seamless production integration.

- Leverage project management tools (e.g., JIRA) for structured execution.

- Maintain robust frameworks for model versioning, documentation, and reproducibility.

- Drive systematic experimentation to refine models and close performance gaps.

- Conduct A/B testing, error analysis, and post-deployment monitoring.

- Establish strong feedback loops between AI performance and business KPIs.

- Encourage innovation by exploring and testing new algorithms.

- Enforce coding, documentation, and version control best practices.

- Stay updated with emerging AI/ML methodologies and translate them into adoption strategies.

- Mentor junior data scientists and foster technical excellence across the team.

- Ensure seamless integration of AI into business workflows.

- Lead discussions with stakeholders to align AI with operational goals.

- Standardize communication for clarity, accountability, and alignment across teams.

- Standardize and scale AI solutions for deployment across business functions.

- Develop reusable AI frameworks to reduce redundancy and improve efficiency.

- Document and share learnings to promote knowledge transfer.

Requirements :

- 4 - 7 years in data science with a proven track record of building and deploying AI/ML solutions.

- Advanced knowledge of ML techniques: regression, classification, time series, optimization, anomaly detection.

- Proficiency in Python, PySpark, and ML frameworks (Scikit-learn, TensorFlow, PyTorch).

- Hands-on experience with cloud & MLOps (Azure ML, Databricks, MLFlow).

- Strong SQL and data visualization skills (Tableau, Power BI).

- Familiarity with IoT, ERP, and sensor data is a plus.

Soft Skills:

- Strong communication and storytelling skills for business impact.

- Solution-oriented mindset with adaptability to dynamic challenges.

- Collaborative approach and ability to influence stakeholders.

- Growth mindset with passion for applying data to solve real-world problems.

Preferred Skills:

- Insurance analytics (underwriting, fraud detection).

- Customer engagement and retention strategies.

- Experience managing cross-functional stakeholders