Senior Engineer/Lead - DS Pharma

Who we are

Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full- stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow.

Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.

We are a Great Place to Work-CertifiedTM (2022-26), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine

Curious about the role? What your typical day would look like?

Key Responsibilities (not limited - other areas within Pharma domain welcome)

• Analytical Translation: Translate complex business and clinical questions from life sciences clients into robust analytical and statistical models.
• Predictive Modeling: Design, train, evaluate, and optimize machine learning algorithms for disease progression, patient outcomes, treatment response, and commercial pharma analytics.
• Quantitative Mastery: Analyze large-scale healthcare and pharma datasets to extract rigorous statistical evidence and support data-driven decision-making.
• Feature & Data Engineering: Develop automated data preparation pipelines in Python and SQL to handle longitudinal, sparse, or noisy medical/enterprise records.
• Algorithmic Optimization: Refine models and objective functions to maximize computational efficiency, stability, and interpretability in regulated environments.
• Production Standards: Package models and analytics scripts following software engineering best practices, utilizing Git workflows and Docker containers.
• Distributed Analytics: Utilize PySpark and cloud architectures to process multi-terabyte patient cohorts and enterprise data assets.
• Client Engagement: Interface directly with pharma/life sciences stakeholders to understand clinical and commercial context and deliver actionable insights.
• Cross-Functional Collaboration: Collaborate with consulting, data engineering, and domain specialist teams to deliver scalable end-to-end analytical solutions.

What do we expect?

• 2.5 to 6 years of relevant Data Science experience with demonstrated success in developing and deploying statistical and machine learning models in production.
• Core proficiency in machine learning (regression and classification) and mathematical optimization, with deep awareness of model assumptions, trade-offs, and limitations.
• Applied experience in Pharma, Healthcare, or Life Sciences analytics, working with clinical trial data, claims, electronic health records (EHR), or Real-World Data (RWD).
• Strong grasp of inferential statistics, biostatistical concepts, hypothesis testing, and quantitative research methodologies.
• Advanced Python programming skills for writing modular, maintainable, and bug-free analytics code using standard libraries (NumPy, Pandas, Scikit-Learn, SciPy).
• High proficiency in SQL for relational data querying, aggregation, and complex cohort transformations.
• Practical experience in production engineering practices: version control via Git and containerization with Docker.
• Exposure to distributed data processing (PySpark, Hive, Hadoop) and cloud platforms (AWS, Azure, or GCP).
• Strong analytical translation capability to convert complex pharma business and scientific problems into structured data science frameworks.
• Strong verbal and written communication skills to present analytical findings to technical teams, consulting partners, and enterprise clients.

You are important to us, let’s stay connected!

Every individual comes with a different set of skills and qualities so even if you don’t tick all the boxes for the role today, we urge you

to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive

culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire.

Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry.