Data Scientist

Greatings from Novac!

We are seeking a skilled Data Scientist with 2–4 years of experience to build scalable data solutions, develop machine learning models, and transform complex data into actionable business insights. The ideal candidate should have a strong foundation in data engineering, analytics, statistics, and machine learning.

Location: Chennai

Experience: 2–4 Years

Employment Type: Full-Time

Required Skills

• Strong proficiency in Python and SQL
• Experience designing and developing ETL/ELT pipelines
• Hands-on experience with data processing frameworks such as Apache Spark
• Experience with relational and NoSQL databases
• Strong understanding of data warehousing, data lakes, and dimensional modeling
• Experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud
• Experience with workflow orchestration tools such as Apache Airflow
• Proficiency in data analysis using Pandas and NumPy
• Experience building and deploying machine learning models using Scikit-learn
• Strong knowledge of statistics, probability, hypothesis testing, and predictive analytics
• Experience with feature engineering, model evaluation, and model optimization
• Data visualization experience using Power BI or Tableau
• Experience with version control using Git
• Understanding of data quality, governance, and security best practices
• Experience in Insurance and Lending domains will be preferred

Good to Have

• Experience with Databricks
• Knowledge of Apache Kafka and real-time data pipelines
• Exposure to TensorFlow or PyTorch
• Experience with MLOps and model deployment
• Knowledge of Generative AI and LLM-based applications

Key Responsibilities

• Design, build, and maintain scalable data pipelines and data platforms
• Collect, clean, transform, and analyze large datasets
• Develop and deploy machine learning models to solve business problems
• Create dashboards, reports, and data visualizations for stakeholders
• Optimize data workflows and ensure data quality and reliability
• Collaborate with business, product, and engineering teams to deliver data-driven solutions
• Monitor, maintain, and improve production data and ML systems