We are looking for a highly analytical and business-oriented Senior Data Scientist to drive advanced analytics, machine learning, and AI initiatives across the organization.

The ideal candidate will work closely with business stakeholders, engineering teams, and leadership to solve complex business problems using data-driven approaches.

This role requires strong expertise in statistical modeling, predictive analytics, machine learning, experimentation, and data storytelling, along with the ability to mentor junior team members and lead end-to-end data science projects.

Key Responsibilities :

- Design, build, and deploy scalable machine learning models for business use cases.

- Develop predictive, classification, recommendation, and forecasting models.

- Perform exploratory data analysis (EDA) and feature engineering on large datasets.

- Apply advanced statistical techniques to identify trends, patterns, and actionable insights.

- Improve model performance through experimentation, tuning, and optimization.

- Translate business challenges into analytical frameworks and data science solutions.

- Partner with product, engineering, marketing, finance, and operations teams to deliver measurable business impact.

- Present insights and recommendations to leadership in a clear and actionable manner.

- Drive data-driven decision-making across functions.

- Work with structured and unstructured datasets from multiple sources.

- Collaborate with data engineering teams to build scalable data pipelines.

- Support MLOps practices including model deployment, monitoring, and retraining.

- Ensure data quality, governance, and compliance standards are maintained.

- Mentor junior data scientists and analysts.

- Lead cross-functional data science initiatives and innovation programs.

- Contribute to AI/ML strategy, best practices, and technology evaluations.

- Stay updated with emerging AI, machine learning, and analytics trends.

Required Skills & Qualifications :

Educational Qualification :

- Bachelors/Masters degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.

- PhD preferred for research-heavy roles.

Technical Skills :

- Strong proficiency in Python/R and SQL.

- Hands-on experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.

- Experience with statistical modeling, NLP, deep learning, or time-series forecasting.

- Knowledge of cloud platforms such as AWS, Azure, or GCP.

- Familiarity with big data technologies like Spark, Hadoop, or Databricks.

- Experience with visualization tools such as Power BI, Tableau, or Looker