Data Scientist - For a leading client (Permanent Job)

Tejoma; Pune District, Mumbai, Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Tejoma is seeking a highly experienced Data Scientist with a strong background in pharma or life sciences commercial analytics. The role focuses on leveraging advanced analytics, statistical modeling, and machine learning to drive sales optimization, marketing effectiveness, market access, and customer engagement.

You will build predictive and descriptive models, develop scalable data pipelines, and communicate insights through dashboards.

Qualifications

• Bachelor's or Master's degree in a quantitative field such as Data Science, Statistics, CS, Mathematics, or Engineering.
• 24 years of data science experience in Pharma/Life Sciences Commercial Analytics.
• Strong understanding of pharma commercial processes: sales, marketing, customer analytics, market performance.

Responsibilities

• Develop predictive and descriptive models to support commercial objectives.
• Analyze large healthcare/pharma data to extract business insights.
• Build ML/Statistical models for segmentation, forecasting, and campaign effectiveness.
• Design data pipelines, feature engineering, and model validation processes.
• Collaborate with stakeholders to translate business problems into analytics and BI dashboards.
• Monitor model performance and iterate based on business feedback.
• Work with data engineering, business consulting, and commercial teams.
• Ensure data quality and governance adherence.

Skills

Analytical thinking

Domain knowledge Pharma/Life Sciences

Data storytelling

Stakeholder collaboration

Education

Bachelors/Masters in data science/ statistics/ CS/ math/ engineering

Tools

Python

SQL

Tableau/Power BI

Spark/PySpark

Databricks

Cloud: AWS/Azure/GCP

Git

Job description

Interview date : 31st October 2026 (Saturday) OR 1st November 2026 (Sunday), Face to face @ Pune.

Interview Location : Pune.

Work location/placement: Bengaluru

We are looking for a highly motivated Data Scientist with 24 years of experience in the pharmaceutical or life sciences domain, specializing in commercial analytics. The ideal candidate will leverage advanced analytics, statistical modeling, and machine learning techniques to generate actionable insights that support commercial decision-making, including sales, marketing, market access, and customer engagement.

Key Responsibilities:

• Develop predictive and descriptive analytical models to support commercial business objectives.
• Analyze large-scale healthcare, pharmaceutical, sales, claims, prescription (Rx), patient, and market data to uncover business insights.
• Build machine learning and statistical models for customer segmentation, targeting, forecasting, next best action, and campaign effectiveness.
• Design and implement data pipelines, feature engineering, and model validation processes.
• Collaborate with commercial stakeholders to translate business problems into analytical solutions.
• Create dashboards and visualizations to communicate findings effectively using BI tools.
• Monitor model performance and recommend improvements based on business feedback.
• Work with cross-functional teams including data engineering, business consulting, and commercial excellence teams.
• Ensure data quality, documentation, and adherence to data governance standards.

Required Qualifications:

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.
• 24 years of experience in Data Science with a focus on Pharma or Life Sciences Commercial Analytics.
• Strong understanding of pharmaceutical commercial processes, including sales analytics, marketing analytics, customer analytics, and market performance measurement.
• Hands-on experience with machine learning algorithms, statistical analysis, and predictive modeling.
• Proficiency in Python or R for data analysis and model development.
• Strong SQL skills for data extraction and manipulation.
• Experience with data visualization tools such as Tableau or Power BI.
• Familiarity with cloud platforms (AWS, Azure, or GCP) is preferred.
• Understanding of Agile methodologies and version control tools such as Git is an advantage.

Technical Skills:

• Python (Pandas, NumPy, Scikit-learn)
• SQL
• R (preferred)
• Machine Learning
• Statistical Modeling
• Data Visualization (Tableau/Power BI)
• Spark or PySpark (preferred)
• Databricks (preferred)
• Cloud Platforms (AWS, Azure, or GCP)