Senior Data Scientist

Industry: Holding Companies & Conglomerates
Company size: 10K+

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Job description

An NYSE-listed pharmaceutical giant that is utilizing cutting-edge research, manufacturing, and distribution solutions to help customers across the globe live in a healthier manner, is looking for a Senior Data Scientist. The candidate will be working closely with engineers, designers, and product managers in cross-functional teams to develop project needs and make contributions to product roadmaps. The company has been utilizing their century-old expertise to successfully revolutionize the healthcare industry. Those who are keen to work with a global company and get knowledge from professionals in the field can seize this fantastic opportunity. 


Job Responsibilities:

  • Create and manage data models and analytics to create scalable and effective products
  • Write and evaluate efficient, thoroughly tested code to ensure a high-quality code base
  • Lead and push analytics and strong, scalable application development
  • Demonstrate an openness to learning and sharing, and keep up with cutting-edge techniques

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 6+ years of relevant experience as a data scientist
  • 6+ years of experience working with Modeling/Machine Learning with Python frameworks
  • Demonstrable experience with PyTorch, Natural Language Processing (NLP), Tensorflow/Keras, and Linux
  • In-depth knowledge of huggingface, sci-kit-learn, pandas, and xgboost
  • Solid understanding of Streamlit and other UI layers
  • Extensive experience applying & implementing solutions with NLP, including Classification, Entity Extraction, training and parameter optimization
  • Solid understanding and experience of Deep Learning 
  • Prior experience with coding: modular design, algorithms, commenting, object-oriented approaches
  • Extensive experience using GitHub or similar Git-based version control
  • In-depth knowledge of Linux/Terminal environment, Docker containers, and CLI patterns
  • Familiarity with Langchain or other LLMOps packages is preferred
  • Nice to have some experience experimenting with tracking with frameworks such as MLFlow
  • Prior experience with Snowflake and Azure Databricks is desirable
  • Some experience leading or mentoring junior data scientists, or leading projects is nice to have
  • Experience with PySpark and Databricks is  preferred but not required
  • Prior experience working with deployment teams or productionalization of models is desirable
  • Nice to have some GNN, PyTorch-geometric, and legal domain knowledge
  • In-depth knowledge of relational databases, data warehouses, operational data stores, in-memory databases, SQL and NoSQL technologies and concepts is preferred
  • Excellent spoken and written English communication skills

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