Data Scientist – Databricks (4+ years of experience)

Company Description Archimedis Digital is a global professional IT services company focused exclusively on Life Sciences, building digital products and solutions that support innovation across the sector. The company partners with Life Sciences organizations to drive growth throughout the digital life cycle, from strategy to execution. Combining deep Life Sciences domain knowledge with strong IT expertise, Archimedis Digital addresses complex cross-functional business challenges with practical, scalable solutions. Its offerings are designed to simplify digital transformation, helping clients modernize operations and unlock new value. Team members collaborate closely with clients in a dynamic, problem-solving environment oriented toward measurable impact.
Role Summary
We are seeking a Data Scientist with strong Databricks and machine learning experience to develop, deploy, and monitor data-driven models. The role will work closely with business, data engineering, and technology teams to convert business problems into scalable analytics and AI/ML solutions.
Key Roles & Responsibilities
Understand business problems and translate them into data science, predictive analytics, or machine learning use cases
Explore, clean, transform and validate structured and unstructured data from multiple data sources
Develop statistical, machine learning, and predictive models using Python and Databricks
Build end-to-end ML pipelines in Databricks for data preparation, feature engineering, model training, evaluation, and deployment
Use Databricks capabilities such as notebooks, Spark, Delta Lake, MLflow, and Databricks Workflows for scalable model development and lifecycle management
Evaluate model performance using appropriate metrics; perform tuning, validation, and error analysis
Collaborate with Data Engineers to ensure reliable data ingestion, data quality, feature availability, and production-ready pipelines
Support model deployment through APIs, batch scoring, or integration with downstream applications and reporting platforms
Implement model monitoring for performance drift, data drift, accuracy, bias, and retraining requirements
Document datasets, assumptions, model logic, performance results, limitations, and deployment/release details
Present findings, insights, and recommendations clearly to business and technical stakeholders.
Follow data governance, security, privacy, and responsible-AI requirements applicable to the client environment
Participate in code reviews, peer reviews, agile ceremonies, and continuous improvement initiatives
Essential Skills / Experience
4–8 years of experience in Data Science, Machine Learning, Advanced Analytics, or related roles
Strong hands-on experience with Databricks and Apache Spark/PySpark
Strong Python experience, including Pandas, NumPy, Scikit-learn and relevant ML libraries
Experience developing classification, regression, clustering, forecasting, NLP, or recommendation models
Experience with SQL and large-scale data processing
Hands-on experience with MLflow, model versioning, experiment tracking, and model deployment is preferred
Understanding of Delta Lake, data lake/lakehouse concepts, and cloud platforms such as Azure, AWS, or GCP
Experience with Git, CI/CD, APIs, and MLOps practices is desirable
Good stakeholder communication and ability to explain model outcomes in simple business terms
Preferred
Databricks certification
Experience with Azure Databricks, Azure ML, AWS SageMaker, or similar platforms
Experience in regulated industries, healthcare, medical devices, pharma, or data privacy-sensitive environments
Knowledge of Responsible AI, explainability, bias assessment, and model governance
Experience with Power BI/Tableau for insight visualization
Job Location: Guindy, Chennai
Salary: Commensurate with current experience

Work arrangement
No