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 casesExplore, clean, transform and validate structured and unstructured data from multiple data sourcesDevelop statistical, machine learning, and predictive models using Python and DatabricksBuild end-to-end ML pipelines in Databricks for data preparation, feature engineering, model training, evaluation, and deploymentUse Databricks capabilities such as notebooks, Spark, Delta Lake, MLflow, and Databricks Workflows for scalable model development and lifecycle managementEvaluate model performance using appropriate metrics; perform tuning, validation, and error analysisCollaborate with Data Engineers to ensure reliable data ingestion, data quality, feature availability, and production-ready pipelinesSupport model deployment through APIs, batch scoring, or integration with downstream applications and reporting platformsImplement model monitoring for performance drift, data drift, accuracy, bias, and retraining requirementsDocument datasets, assumptions, model logic, performance results, limitations, and deployment/release detailsPresent findings, insights, and recommendations clearly to business and technical stakeholders.Follow data governance, security, privacy, and responsible-AI requirements applicable to the client environmentParticipate in code reviews, peer reviews, agile ceremonies, and continuous improvement initiativesEssential Skills / Experience 4–8 years of experience in Data Science, Machine Learning, Advanced Analytics, or related rolesStrong hands-on experience with Databricks and Apache Spark/PySparkStrong Python experience, including Pandas, NumPy, Scikit-learn and relevant ML librariesExperience developing classification, regression, clustering, forecasting, NLP, or recommendation modelsExperience with SQL and large-scale data processingHands-on experience with MLflow, model versioning, experiment tracking, and model deployment is preferredUnderstanding of Delta Lake, data lake/lakehouse concepts, and cloud platforms such as Azure, AWS, or GCPExperience with Git, CI/CD, APIs, and MLOps practices is desirableGood stakeholder communication and ability to explain model outcomes in simple business termsPreferred Databricks certificationExperience with Azure Databricks, Azure ML, AWS SageMaker, or similar platformsExperience in regulated industries, healthcare, medical devices, pharma, or data privacy-sensitive environmentsKnowledge of Responsible AI, explainability, bias assessment, and model governanceExperience with Power BI/Tableau for insight visualizationJob Location: Guindy, Chennai Salary: Commensurate with current experience