AVP, Data Analytics and Artificial Intelligence (AI)

Job description

Overview

Data Analytics and Artificial Intelligence (AI) methods can speed up drug discovery, cut R&D costs, decrease failure rates in drug trials and eventually create better medicines, to improve the lives of our patients. There is a wide range of applications along the pharma R&D value chain, including

·  Identification of new pathways and targets using “-omics” analysis, identification of novel therapeutic targets & biomarkers, personalized medicine based on “-omics” markers, discovery of connections between drugs and disease phenotypes
·  Development of new therapeutics, through property prediction, novel drug combinations, drug repositioning and analysis of protein features and characteristics
·  Increasing efficiency and reducing manual work, through analysis of biomedical & process information as well as clinical trial and patient-related data, natural language processing & automated document generation
·  Improving outcomes and PoS, through aggregation and analysis of relevant data, forming and qualifying hypotheses, assessing risk, designing and optimizing clinical trial scenarios, and enabling better decision-making overall

We are looking for a senior leader in Data Analytics and Artificial Intelligence (AI) Methods, to globally lead scientists from various data science disciplines. He/she will be reporting into the Head of Digital & Data Sciences (DDS), a new platform within Sanofi R&D.

The responsibilities of the Data Analytics and AI Methodology leader will include:

·  Building up globally and leading our efforts in Data Analytics and AI Methodology, including identification, hiring and mentoring talent
·  Within DDS leading globally our efforts in Data Analytics and AI Methods, with focus on evaluation, development and application of various algorithms, methods and tools along the entire R&D value chain, including
·  Assessing data quality and integrity in collaboration with other teams and stakeholders
·  Leading data mining and collection procedures
·  Interpreting and analyzing data problems
·  Building analytic predictive models
·  Experimenting with new models and techniques
·  Aligning data analytics and AI projects with organizational goals
·  Managing activities and internal resources, including science, project issues, staff and budgets. Conceiving, planning and prioritizing data projects.
·  Developing and maintaining a strong working relationship with other data science groups within DDS, as well as in other departments and functions of R&D.
·  Working collaboratively with internal and external partners (e.g. CROs) to coordinate the planning and execution of day-to-day deliverables
·  Maintaining a keen awareness of developments in data technologies, analytics, methods and systems, especially regarding AI&ML approaches
·  Evaluating and coordinating academic collaborations and outsourcing partners (CROs) in the field
·  Updating and reporting of relevant results to stakeholders

Qualifications & Requirements

·  An MS or PhD in a field related to Data Analytics, AI or Machine Learning such as: Computer Science, Mathematics, Statistics or Physics
·  10+ years of experience in the pharmaceutical industry with a strong record of accomplishments and experience in evaluation, development and application of AI&ML approaches.
·  Strong familiarity with Deep Learning techniques, various network architectures (CNNs, GANs, RNNs, Auto-Encoders, etc.), regularization, embeddings, loss-functions, optimization strategies, etc.
·  Familiarity with one or more typical deep learning frameworks: TensorFlow, Caffe, MxNet, TORCH, etc.
·  Good knowledge of R, Python and MATLAB
·  Experience with SQL and NoSQL databases
·  Knowledge of Extract, Transform and Load (ETL) frameworks
·  Knowledge of Enterprise Data Warehouse (EDW) and data management systems
·  Specific knowledge & experience in one or more of the following would be a plus: image analysis, natural language processing, automated document generation, reinforcement learning, control theory, knowledge representation (semantic models, graph databases, etc.), distributed systems and high-performance computing methods.
·  Strong methodological capabilities and broad experience across different stages of the pharma R&D process
·  Demonstrated leadership experience and demeanor to spearhead implementation of novel data science-related methods
·  A change agent with a combination of business, science & technology, and diplomatic skills

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

#GD-SA

At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.