Havas Life Mumbai
Website:
in.havas.com
Company:
https://www.linkedin.com/company/havaslifemumbai
Industries: Advertising Services and Marketing Services
Job details:
Title: Senior Data Scientist (Contract)
Reports to: Head of Data Science
Team: Data Strategy & Analytics, Experience Practice
Duration: 6-9 months
About Company:
Havas Life Mumbai is a leading healthcare and wellness communications agency that is part of the global Havas Group. We combine creativity, strategy, science, and technology to help healthcare, pharmaceutical, biotech, medical device, and wellness brands connect meaningfully with healthcare professionals, patients, caregivers, and consumers. Our expertise spans brand strategy, creative campaigns, digital experiences, medical communications, content, social media, patient engagement, and integrated marketing creating work that inspires healthier lives.
Overview of the Role:
As a Senior Data Scientist on a contract basis, you will be a key hands-on contributor to our data science initiatives. You will primarily focus on executing projects that harness and optimize critical data sources, including US claims data, audience intelligence platforms, and other complex datasets. Using your expertise in Python, statistical analysis, machine learning, and emerging tools like Large Language Models (LLMs), you will develop and deploy robust analytical solutions that generate actionable insights for our healthcare and pharma clients. This role is focused on project delivery and tangible execution, supporting the team by turning data challenges into clear, data-driven outputs.
Key Responsibilities
- Project Execution & Model Development:
- Execute Python-based modeling and analysis on complex datasets (e.g., claims, social, audience data) to uncover patterns, predict behaviors, and generate actionable insights.
- Develop, validate, and deploy analytical models, including segmentation, targeting frameworks, and measurement approaches.
- Support and contribute to projects involving the application of Large Language Models (LLMs) for data analysis and insight generation.
- Support the data engineering workflow by cleaning, transforming, and preparing data for analysis, ensuring quality and usability.
- Cross-Functional Collaboration:
- Collaborate closely with analytics, strategy, media, and CX teams to provide the data-driven components for omnichannel solutions and customer journey analysis.
- Translate data-driven findings into clear and compelling narratives for internal stakeholders and, when required, client-facing presentations.
- Act as a hands-on resource for data-related questions and provide analytical support for ongoing client projects.
- Analytical Rigor & Best Practices:
- Apply robust data analysis techniques to ensure the statistical validity and reliability of all results.
- Work within established frameworks for data privacy, security, and ethical use, particularly concerning sensitive patient-level and US claims data.
- Document methodologies, code, and findings clearly to ensure project continuity and knowledge sharing within the team.
Qualifications:
- Data Science Experience: 5-7+ years of hands-on experience in a data science or analytics role with strong, demonstrated expertise in Python for data manipulation (Pandas, NumPy), statistical analysis, and machine learning (scikit-learn).
- Technical Skills:
- Proficient in SQL and experience working with large datasets within a Google Cloud Platform (GCP) environment.
- Experience or strong demonstrated interest in applying Large Language Models (LLMs) to analytical problems.
- Familiarity with data visualization tools (e.g., Tableau, Power BI) is highly desirable.
- Problem-Solving & Adaptability: Proven ability to quickly learn and work with complex, unfamiliar data domains. Must be a proactive, hands-on problem-solver who can deliver actionable insights from ambiguous data.
- Communication: Strong ability to explain complex analytical methods and results to stakeholders with varying levels of technical expertise.
- Domain Exposure (Preferred): Experience with healthcare/pharma data (e.g., claims data) or with audience intelligence platforms (e.g., YouGov, social media analytics) is a strong plus but not a strict requirement for a candidate with an otherwise strong technical background.
- Education: An advanced degree (e.g., M.S.) in Data Science, Statistics, Computer Science, or another quantitative field is preferred.
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