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A Range of Possibilities

Scientist Deep Data Analytics

date posted 10/10/2019
contract type Full time
job id R2517293
location Cambridge, Massachusetts

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 probability of success (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 scientist in Deep Data Analytics, to become a member of a newly formed global team from various data science disciplines. He/she will be reporting into the global Head of Deep Data Analytics. The global team of Deep Data Analytics is part of a new Digital Data & Sciences platform within Sanofi R&D

The responsibilities of the scientist in Deep Data Analytics will include:     

  • Apply artificial intelligence and machine learning approaches (e.g. classification, clustering, artificial neural networks, deep learning) on clinical data sets (biomarker profiles, genome-wide datasets, medical imaging data, continuous data from wearable devices)
  • Support patient classification by generating hypothesis for biomarkers to identify treatment responders, align with biostatisticians for hypothesis validation
  • Update and report relevant results to interdisciplinary project teams and stakeholders
  • Develop and maintain strong working relationship with other modeling groups within TI organization, as well as with biostatisticians outside of the TI organization.
  • Maintain a keen awareness of developments in data technologies, analytics, methods and systems especially for AI&ML approaches for the analysis of clinical data, special interest for analysis on data from wearable devices and imaging data
  • Evaluate and coordinate academic collaborations and outsourcing partners (CROs) in area of application of AI&ML for clinical data analysis, in particular for analysis of data from wearable devices and imaging data

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
  • 0+ years experience in in the pharmaceutical industry with a strong record of accomplishments and experience in evaluation, development and application of AI&ML approaches
  • Familiarity with Deep Learning techniques, various network architectures (CNNs, GANs, RNNs, Auto-Encoders, etc.), regularization, embeddings, loss-functions, optimization strategies, or reinforcement learning techniques such as REINFORCE, DQN, PPO, etc.
  • Familiarity with one or more typical deep learning or reinforcement learning frameworks: TensorFlow, Keras, Caffe, MxNet, TORCH, OpenAI Gym, Keras-RL etc.
  • Good knowledge of R, Python and MATLAB
  • 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

Qualifications & Requirements:

  • A change agent with a combination of business, science & technology, and diplomatic skills
  • Experience with SQL and NoSQL databases

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.

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#LI-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.

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