Digital Data Architect

Job title: Real-World Evidence Data Scientist

About the job

Our Team:

Sanofi Business Operations is an internal Sanofi resource organization based in India and is setup to centralize processes and activities to support Specialty Care, Vaccines, General Medicines, CHC, CMO, and R&D, Data & Digital functions​. Sanofi Business Operations strives to be a strategic and functional partner for tactical deliveries to Medical, HEVA, and Commercial organizations​ in Sanofi, Globally.

Main responsibilities:

The overall purpose and main responsibilities are listed below:

Provide a high level of expertise in employing cutting-edge analytical & computational approaches to drive evidence-based pharmaceutical product development; provide scientific and technical leadership in machine learning and AI; work closely with other disciplines across Sanofi including Business Units, Digital, R&D, Biostatistics, Information Technology Systems and other Data Science partners to deliver cutting edge analysis to key business questions. Examples of Advanced Analytics activities: (1) Machine/Deep Learning to elucidate disease trajectories, patient subtypes, define underdiagnosed conditions, and unmet health needs; (2) Create a framework for generating re-usable models and insights across big-data (e.g. EHRs, claims) and rich small data sets (e.g. clinical trials, imaging); (3) Generating insights by merging diverse data streams e.g. health, surveillance, trend data, sensor, imaging; (4) Adoption of emerging technology into an analytical framework:  distributed analytics, graph databases

• People: (1) Act as a subject matter expert in machine learning, statistical and/or modelling working on team projects; (2) Work with internal and external study lead to execute Advance Analytics projects and studies.
• Performance: (1) Implement and execute computational and statistical methodologies in Advanced Analytics for RWE; (2) Provide expertise and execute advanced analytics for solving problems across R&D, Medical Affairs, HEVA and Market Access Strategies and Plans
• Process: (1) Apply a broad array of capabilities spanning machine learning, statistics, mathematics, modelling, simulation, text-mining/NLP, data-mining to extract insights and be able to communicate and champion these efforts across the company; (2) Plan and deploy methodological standards, standardized processes, demos, and POCs for the company’s highest priority business needs; (3) Contribute to the design, development, and implementation of Sanofi’s data science architecture and ecosystem to guide decision-making and building foundational capabilities

About you

• Experience: Around 10 years’ experience; High level proficiency in at least two or more technical or analytical languages (R, Python, etc..); experience with advanced ML techniques (neural networks/deep learning, reinforcement learning, SVM, PCA, etc.); ability to interact with a variety of large-scale data structures e.g., HDFS, SQL, NoSQL; Experience working across multiple environments (e.g. AWS, GCP, Linux) for optimizing compute and big data handling requirements; Experience with any of the following: biomedical data types/population health data/real world data/novel data streams relevant to the pharmaceutical industry; Experience with big data analytics platforms or high-level ML libraries such as H2O, SageMaker, Databricks, Keras, pyTorch, TensorFlow, Theano, DSSTNE or similar; Ability to prototype analyses and algorithms in high-level languages embracing reproducible and collaborative technology platforms (e.g. GitHub, containers, jupyter notebooks); Exposure to NLP technologies and analyses; Knowledge of some datavis technologies (ggplot2, shiny, plotly, d3, Tableau or Spotfire); Experience with probabilistic and/or functional programming languages such as Stan, Edward, Scala; Experience with advanced ML techniques (RNN, CNN, LSTM, GRU, Genetic Algorithms, Reinforcement Learning, etc.)
• Real-World Data (RWD): Experience with Real-World Data (RWD), demonstrated proficiency in working with diverse real-world data sources, including but not limited to: MarketScan, CPRD, TriNetX and STATinMED.

• Education: PhD in quantitative field such as Statistics, Biostatistics, Applied Mathematics or related field with 6 years of industry or academic experience; Relevant Master’s Degree, with 10 years of related industry or academic experience.
• Soft skills: Strong oral and written communication skills; ability to work and collaborate in a team environment

• Languages: Excellent knowledge of English language (spoken and written)

Pursue progress, discover extraordinary

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.

Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!