Senior Data Scientist (AI Products)
phamax
- Experience
- 6–8 years
- Location
- Bangalore (Hybrid) - Full-time · Hybrid
- Job type
- Full-time
- Python
- Machine Learning
- SQL
- Cloud Platforms (Azure/AWS/GCP)
- LLMs/GenAI/RAG
About the role
Architect and Deploy AI-Powered Products. Engineer Scalable Data Pipelines. Operationalize ML Lifecycle (MLOps). Translate Pharma Problems into AI Solutions. Mentor and Build Data Science Culture. Optimize Model Performance and Efficiency.
What you’ll do
- Design, build, and deploy scalable machine learning and AI models, specifically focusing on LLMs, RAG, and agentic systems, to drive product capabilities in the pharma domain.
- Develop and optimize robust data ingestion, processing, and feature engineering pipelines to handle large, complex structured and unstructured datasets.
- Implement end-to-end MLOps practices including model training, deployment, monitoring, and maintenance to ensure continuous improvement and efficiency.
- Collaborate with stakeholders to understand complex pharmaceutical business challenges (market access, HEOR) and translate them into actionable data science solutions.
- Mentor junior team members, conduct code reviews, and foster a culture of continuous learning and innovation within the data science team.
- Continuously evaluate, benchmark, and improve model performance, scalability, and efficiency to ensure business value and cost-effectiveness.
What we’re looking for
Must have
- Python
- Machine Learning
- SQL
- Cloud Platforms (Azure/AWS/GCP)
- LLMs/GenAI/RAG
Nice to have
- NLP
- Computer Vision
- Streaming Systems (e.g., Kafka)
What makes this role challenging
- Experience operating in a fast-paced startup environment with high ambiguity
- Ability to handle sensitive healthcare data with strict privacy compliance
- Experience scaling systems to support high-volume transactional data
- Unable to discuss the trade-offs between different vector databases or embedding models.
- Demonstrates lack of understanding regarding data privacy laws (GDPR/HIPAA) in the context of model training.
- Focuses solely on model accuracy metrics without considering business impact or deployment constraints.
- Cannot describe a past incident where a production model failed and how they resolved it.
Job description
Senior Data Scientist (AI Products)
Job summary
Job Title: Senior Data Scientist (AI Products)
Key responsibilities
Department: IT
Required skills &
Qualifications
Good to have
Desired Experience Range: Minimum 6-8 years
Why Join Us?
Job summary
We are seeking a talented and driven Senior Data Scientist to join our fast-
growing startup focused on building innovative AI-powered products. This
role involves working at the intersection of machine learning, data
engineering, and product development, transforming complex data into
impactful solutions.
You will play a key role in designing, developing, and deploying scalable AI
models that directly influence product capabilities and business outcomes.
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Key responsibilities
- Design, build, and deploy machine learning and AI models for real-world
applications.
- Work with large, complex datasets to extract insights and drive decision-
making.
- Develop and optimize data pipelines, feature engineering, and model
training workflows.
- Collaborate with product managers, engineers, and stakeholders to
translate business problems into data solutions.
- Evaluate model performance and continuously improve accuracy, scalability,
and efficiency.
- Implement and maintain end-to-end ML lifecycle (ML Ops) practices
- Conduct exploratory data analysis (EDA) and communicate findings
effectively.
- Stay updated with the latest advancements in AI, ML, and data science.
- Mentor junior team members and contribute to building a strong data
science culture.
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Required skills & qualifications
- 6–8 years of experience in Data Science / Machine Learning roles.
- Strong proficiency in Python or R with hands-on experience in ML libraries
(e.g., TensorFlow, PyTorch, Scikit-learn).
- Solid understanding of machine learning algorithms, statistics, and data
modelling.
- Experience working with large datasets and distributed systems.
- Strong skills in data preprocessing, feature engineering, and model
evaluation.
- Experience with SQL and data manipulation tools.
- Familiarity with cloud platforms (Azure, AWS, GCP).
- Ability to translate complex problems into scalable AI solutions.
- Strong analytical thinking and problem-solving skills.
- Strong knowledge of data ingestion, data pipelines, and large-scale data
processing.
- Hands-on understanding of LLMs, Generative AI, RAG, and multi-agent AI
systems.
- Experience working on AI-powered products involving structured and
unstructured data.
- Exposure to agentic AI workflows, prompt engineering, vector databases,
and model evaluation.
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Good to have
- Experience with deep learning, NLP , computer vision, or generative AI.
- Knowledge of ML Ops tools and frameworks (e.g., MLflow, Kubeflow,
Airflow).
- Experience deploying models using APIs, Docker, or Kubernetes.
- Exposure to real-time data processing and streaming systems.
- Prior experience working in a startup or fast-paced environment.
- Experience with Pharma or Life Sciences domain is an added advantage.
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Why Join Us?
- Opportunity to work on cutting-edge, innovative AI products
- High-impact role with ownership and visibility
- Fast-paced, collaborative startup culture
- Freedom to experiment and build next-generation AI solutions
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