Location: Hyderabad
Job Time: Full Time
Salary: 80,000
A healthier future. It’s what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love.
That’s what makes us Roche.
Roche has established the Global Analytics and Technology Center of Excellence (GATE) to drive analytics- and technology-driven solutions by partnering with Roche affiliates across the globe. GATE enables data-led decision-making and innovation across healthcare and biotech operations.
As a Senior Data Scientist, you will lead and deliver high-impact data science projects that enable strategic decision-making within Roche’s healthcare and commercial ecosystem. Collaborating closely with cross-functional teams, your primary focus will be on Healthcare and Pharma Data Science and Marketing Mix Modeling (MMM) leveraging advanced statistical and machine-learning techniques to generate actionable insights and optimize business outcomes.
Exposure to GenAI, LLM, NLP, and ML Ops will be considered a strong advantage, supporting Roche’s future-ready analytics and AI roadmap.
Your Opportunity:
Project Leadership and Collaboration (Primary Focus):
Lead and manage end-to-end data science projects from problem definition to model deployment ensuring alignment with business goals and timelines
Partner with cross-functional teams to define business requirements and deliver tailored analytics solutions
Develop and maintain key stakeholder relationships to ensure effective communication and collaboration throughout project lifecycles
Present analytical findings and strategic recommendations to business stakeholders, influencing data-driven decision making across multiple levels of the organization
Advanced Analytics (Primary Focus):
Collect, clean, and prepare large and complex healthcare-related datasets (product performance, patient data, operational metrics, etc.) for analysis
Develop and implement statistical and machine learning models (e.g., multivariate regression, time-series analysis, XGBoost, clustering, classification, causal inference) to address complex business problems and uncover meaningful insights
Utilize advanced data analytics techniques to explore and identify patterns, trends, and root causes, applying methodologies such as clustering, classification, and causal inference
Marketing and Experimental Analytics (Primary Focus):
Build Econometric/market mix models (MMM), multi-touch attribution models (MTA), optimize marketing spend and come-up with implementable recommendations and strategy/plan
Lead the development and implementation of advanced Media Mix Models to inform and optimize marketing spend across multiple channels (e.g., TV, digital, print, radio)
Design and execute complex statistical analyses to evaluate the effectiveness of marketing strategies and optimize resource allocation
Apply experimental design and A/B testing methodologies to validate and measure marketing and operational initiatives
GenAI, NLP, and Machine Learning Operations (Secondary / Emerging Focus):
Develop and implement GenAI models and tools to solve business problems
Deploy machine learning models in production environments, ensuring robust ML Ops practices for model monitoring, maintenance, and scaling
Collaborate with IT and DevOps teams to streamline the integration of ML models into existing systems and workflows
Enhance agent performance through experimentation with LLMs, prompt tuning, and advanced reasoning workflows
Communication, Mentorship, and Governance (Primary Focus):
Translate complex data insights into clear and actionable business strategies that address stakeholder needs and expectations
Mentor and guide junior data scientists, providing technical expertise and fostering an environment of continuous learning and improvement
Promote best practices in coding, data handling, and project management within the data science team, ensuring high-quality deliverables
Ensure adherence to Roche’s ethical AI standards and data privacy regulations
Who you are:
You hold a bachelor’s degree in Technology or a relevant discipline, with a preference for Computer Science, Software, Statistics, Data Science, AI, Machine Learning, Data Engineering and related fields. Preferably, you have a Master’s degree
Certifications in AI/ML, Data Science, or related technologies would be a plus
You have 5-8 years of hands-on experience in data science, with proven experience in leading data science projects within the pharma/biotech/healthcare domain
Strong proficiency in Python and SQL, with experience in data wrangling, feature engineering, and analytical model development
Experience working in cloud-based environments (AWS preferred), with practical knowledge of GitHub and cloud computing workflows for data science projects
Hands-on experience building models using algorithms and techniques such as multivariate regression, time series analysis, XGBoost, clustering, classification, OLS regression, Naïve Bayes, linear and time-decay attribution models, Markov chains, and Shapley value methods
Experience in Multi channel Marketing Mix Modeling (MMM), or related fields, with a track record of delivering impactful results
At least 4 years of strong experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, spaCy, NLTK, NumPy, pandas, and Spark
Basic understanding of pharmaceutical datasets (e.g., IQVIA, SHA, Patients data) and familiarity with US healthcare markets would be a plus
Strong analytical and problem-solving skills with a data-driven mindset
Good to Have:
Experience with modern deep learning architectures for NLP, including hands-on experience with transformers (e.g., Hugging Face, SBert, GPT-2/GPT-3) and the capability to build ML/DL pipelines for training/tuning models, including transfer learning
Proficiency with LLM APIs (e. g. , OpenAI, Claude, Gemini) and agent frameworks such as AutoGen, LangGraph, AgentBuilder, or CrewAI
Experience with prompt engineering or intelligent workflow automation
Bash/shell scripting is a plus, Experience with Docker, API development is advantageous