Data Science Job in Biogen Capability Center India Private limited at Bangalore
FEATURED JOBData Science
organization.
Job Description
Role : Developer - Data Science
Job Description :
Developer - Data Science will be responsible for building data engineering pipelines and building/deploying data science, machine learning, data analytics solutions and knowledge graphs. Operationalize ML pipelines in distributed data processing environments like Apache Spark, using tools like ML flow covering Model Tracking, Model Registry and other aspects of Model Training. Collaborate with Stakeholders such as Business users, Data Scientists and PO&T IT Functional Leads to design & build solutions using variety of programming tools such as Python, PySpark, Scala, Sql, R. etc.
Responsibilities Include:
1. Building data engineering pipelines and building/deploying data science, machine learning, data analytics solutions and knowledge graphs.
2. Creating, updating the technical documentation (including GxP).
3. Collaborates with MSP support team for deployed AI/ML solutions
4. Work closely with data scientists, software engineers, and product teams to align AI initiatives with business goals.
5. Manage development tools and processes to monitor model performance and update them as needed to maintain accuracy.
6. Design, develop and maintain robust BI solutions to turn raw data into actionable insights.
Key Experience :
1. 5–7 years of experience in AI/ML engineering and Python, with hands-on experience building enterprise-scale AI applications on modern data science platforms.
2. 3-5 years of Experience with Databricks, LangChain, LangSmith, and other advanced GenAI platforms supporting prompt orchestration, traceability and monitoring.
3. Experience with MLOps practices including CI/CD, model/application evaluation, version control, automated testing and production deployment.
4. Experience deploying AI/ML applications and backend services in Azure cloud environments.
5. Experience developing Python-based APIs and backend services using FastAPI, Flask, or similar frameworks.
6. Strong understanding of Machine Learning model development including data exploration (EDA), model training and fine tuning techniques.
7. Knowledge on reporting and visualization tools such as Power BI and Tableau.
8. Experience with Life Sciences related business process domains, such as R&D, manufacturing, quality, and supply chain is beneficial
9. Experience collaborating with cross-functional teams to convert business requirements into scalable, secure, and reliable AI solutions.
Specialty Expertise in at least in few of the following areas:
1. Experience in optimizing and scaling big data workloads for high performance and cost efficiency.
2. Hands-on experience with modern development tools and practices, including CI/CD pipelines, unit and integration testing, automation, and workflow orchestration.
3. Strong experience in designing and implementing data solutions on cloud platforms (AWS and Azure), adhering to best practices in cloud security, networking, and architecture.
4. Solid understanding of machine learning lifecycle concepts, including model tracking, model serving, and productionizing ML pipelines in distributed environments such as Apache Spark, leveraging tools such as MLflow.
5. Experience working with NoSQL and/or graph database technologies.
Key Skills :
1. 5-7 years of strong experience in Python, Generative AI and hands on experience in Prompt Engineering, RAG, Vector Databases to build AI solutions.
2. 3-5 years on experience in Databricks, Snowflake, Rest API, Langsmith, CI/CD pipelining, and deployment practices.
3. Hands on experience in visualization tools like Power BI, Tableau
4. Strong understanding of data engineering and pipeline design, including building scalable ETL/ELT workflows for structured and unstructured data.
5. Experience with AI system evaluation and optimization, including prompt tuning, model performance analysis, and improving response quality in production environments.
