DATA Scientist

We are looking for a Data Scientist to develop data-driven solutions that address business and product challenges. The role will involve working across data preparation, exploratory analysis, statistical and machine learning modelling, visualization, and production deployment. The ideal candidate should be strong in Python and SQL, with solid analytical skills and the ability to translate business requirements into practical data science solutions.

Key Responsibilities

• Collect, clean, transform, and analyze structured and unstructured data.
• Develop and implement machine learning and statistical models.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Build predictive models for forecasting, classification, and optimization problems.
• Evaluate model performance and improve model accuracy, reliability, and robustness.
• Create dashboards, reports, and data visualizations to communicate insights effectively.
• Collaborate with engineering, product, business, and analytics teams to solve business problems.
• Translate business requirements into data-driven solutions and measurable outcomes.
• Deploy, monitor, and maintain machine learning models in production environments.
• Maintain clear documentation of datasets, models, methodologies, experiments, and results.

Required Skills

• Strong proficiency in Python and SQL.
• Hands-on knowledge of data preprocessing, feature engineering, model training, and model validation.
• Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
• Strong analytical, statistical, and problem-solving skills.
• Ability to interpret data and communicate insights clearly to technical and non-technical stakeholders.
• Good communication, presentation, and collaboration skills.

Preferred Skills

• Experience with deep learning frameworks such as TensorFlow or PyTorch.
• Knowledge of NLP, computer vision, or Generative AI.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with MLflow, Docker, Kubernetes, or broader MLOps practices.
• Experience working with large datasets and distributed computing frameworks such as Apache Spark.

Role Highlights

• Hybrid work model with opportunities in Bengaluru and Pune.
• End-to-end exposure to data science, machine learning, visualization, and production deployment.
• Cross-functional collaboration with engineering, product, business, and analytics teams.