Data Scientist Advanced Analytics

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We're looking for people who are determined to make life better for people around the world.

About Lilly:

At Lilly, we unite caring with discovery to make life better for people worldwide. We are one of the Top 10 most valued companies of the world, and global healthcare leader headquartered in Indianapolis, Indiana. Our 44,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We're looking for people who are determined to make life better for people around the globe.

We have pioneered the development of several significant drugs and treatments over the years – and strong pipeline including being the first to mass produce insulin, penicillin, tuberculosis (MDR-TB) and polio vaccines.

At Lilly, our research and product-oriented mindset and focus on Accelerate, Reach and Scale using new-gen technologies helps us redefine what is possible through technology in pharma. Impact driven growth combined with a commitment to make a real difference in lives makes Lilly the place of choice for the best talent to come together and be at the forefront of innovation and acceleration.

Join us to make significant difference in the well-being of people worldwide.

At Lilly, we believe in the talent of our workforce. One of the best ways to utilise and develop that talent is to use our existing workforce to fill new and/or open positions. If you are looking for a new position within Lilly, you can view and apply to open roles posted in the internal job posting system. You must meet the minimum qualifications outlined in the job description and have/obtain work authorisation in the country the position is to be considered. When applying internally for a position, your current supervisor will receive notification that you have applied to the position. We encourage employees to discuss the opportunity with their supervisor prior to applying. 

Job Title: Data Scientist

Job Level: Principal Scientist - Data - Advanced Analytics

Experience Level: 7 to 8 Years

Qualification and Eligibility criteria:  B.Tech./Masters/Ph.D. in statistics, Machine Learning, Data Science or related field.

Location: India – Bengaluru

Purpose of the Role:

We are seeking a highly skilled Data Scientist with 7–8 years of experience or an advanced degree (Master's/Ph.D.) in Statistics, Machine Learning, or Data Science. The ideal candidate will be passionate about solving complex business challenges in manufacturing and supply chain domains through advanced analytics. This role demands strong expertise in statistical modelling, machine learning, time-series analysis, and simulation techniques, coupled with the ability to manage large, diverse datasets and derive actionable insights. Proficiency in Python/R programming and familiarity with optimisation techniques are essential. The candidate must demonstrate the ability to translate business problems into technical solutions, communicate effectively with stakeholders, and adapt to evolving business needs while simplifying technical concepts for non-technical audiences.

Key Responsibilities:

Design and develop advanced analytics solutions using various statistics, machine learning, and data science, probabilistic modelling, and optimisation methods for solving problems such as anomaly detection, time series forecasting, root cause analysis, bottleneck detection, predictive maintenance etc. Apply Data Visualization Techniques for effective storytelling through data and share insights with business leaders. Apply advanced statistical techniques (DoE, causal modelling) and time-series forecasting for predictive maintenance and process optimisation. Perform exploratory data analysis (EDA) and feature engineering on structured, semi-structured, and unstructured data from sensors, logs, and production systems. Integrate and manage diverse datasets, ensuring robustness for high-dimensional, imbalanced, and noisy data. Develop scalable solutions for real-time inference, batch processing, and edge computing using modern deployment tools (Docker, Fast-API, Flask etc.). Lead end-to-end model lifecycle: development, deployment, monitoring, and performance optimisation across cloud, on-premises, and edge environments. Stay current with emerging AI/ML research, implementing practical innovations such as simulation and synthetic data generation. Collaborate with cross-functional teams as a trusted advisor, driving projects from kick-off to insight generation and visualisation. Ensure best practices in version control and CI/CD workflows using GitHub, GitHub Actions, and cloud platforms (AWS, Azure).

Essential Tech Knowledge:

Machine Learning, Statistics & Data Science

Expertise in statistical modelling, machine learning algorithms, and probabilistic modelling techniques. Strong skills in data preprocessing, feature engineering, and data mining. Experience with high-dimensional, imbalanced datasets and robust model development. Ability to handle complex data structure and expertise in integration of data from various data sources using Python, APIs, SQL, PySpark etc. Knowledge of data visualisation tools such as Plotly, Power Bi, dash is desirable. Familiarity with optimisation techniques and simulation-based approaches. Knowledge of causal inference and experimental design (DoE) is desired. Familiarity with optimisation techniques, including model quantisation, pruning etc. is a plus. Familiarity and interest towards and implementation of emerging technologies such as Generative AI, reinforcement learning, and digital twin simulations to enhance manufacturing resilience and efficiency is desirable.

Software Development & Programming:

Advanced proficiency in Python/R; experience with C++ is a plus. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, Keras). Ability to deploy ML models to production using lifecycle management tools. Familiarity with cloud platforms (AWS, Azure) and containerization (Docker). Experience with CI/CD pipelines, Git-based version control, and scalable software development. Knowledge of UI/app development for ML use cases is desirable.

Essential Behavioural Skills:

Partner with senior business leaders to identify high-impact opportunities and deliver measurable business outcomes through advanced analytics. Strong problem-solving and critical thinking abilities for open-ended business challenges. Excellent communication skills to simplify technical concepts for non-technical stakeholders. Proven ability to collaborate in cross-functional and globally distributed teams. High adaptability and self-management in dynamic, ambiguous environments. Proven interest in latest advancements in machine learning, data science, statistics, and optimisation and related fields. Commitment to continuous learning, knowledge sharing, and adoption of industry best practices. Ability to manage projects independently, ensuring timely and quality outcomes. Serve as trusted advisor by actively participating in various phases of the projects (including kick-off, methodology development, execution, insight generation and data visualisations) Mentor junior data scientists and engineers, fostering a culture of innovation and technical excellence.

Domain Expertise (Desirable):

Familiarity with digital manufacturing platforms, IoT data streams, and edge AI deployment is desirable. Strong domain knowledge in manufacturing processes, supply chain optimisation, and process optimisation to implement impactful solutions is desirable. Understanding of digital manufacturing ecosystems and Industry 4.0 technologies will be useful.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form ) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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