Data Scientist - Machine Learning

Job DescriptionJob Description

Data Scientist - Machine Learning ROCGJP00027870

A leading biotechnology company is seeking a Data Scientist - Machine Learning. The right candidate will work closely with multi-disciplinary teams to design, develop and deploy structured, high-quality data solutions in particular Large Model (LLM) applications. These solutions will be leveraged across the Product Development organization to help our teams fulfill our mission: to do now what patients need next. We focus on delivering technology that evolves the practice of medicine and helps patients live longer, better lives. We are a diverse team of open and friendly people, enthusiastic about technological novelties and optimal enterprise solutions. We share knowledge, experience & appreciate different points of view.

Data Scientist - Machine Learning Pay and Benefits:

• Hourly pay: $75-$85/hr (pay varies based on candidate's experience)
• Worksite: Leading biotechnology company (South San Francisco, CA 94080)
• W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
• 40 hours/week, 12 Month Assignment

Data Scientist - Machine Learning Responsibilities:

• Partner with fellow Data Scientists, ML engineers, MLOps / DevOps engineers and cross functional teams to solve complex problems and create unique solutions by using modern NLP technologies in particular LLMs.
• Build data pipelines and deployment pipelines for ML models.
• Development of ML models according to business and functional requirements.
• Able to help deploy various models and tune them for better performance.
• Document and communicate the design and implementation details.
• Contribute to the DSE AI team on technical decisions.
• Collaborate with clients, and informatics departments to deploy scalable and easy-to-maintain solutions.
• Serves as a technical point of contact for enterprise-wide technologies solutions. Leads complex troubleshooting efforts and root cause analysis.

Data Scientist - Machine Learning Qualifications:

• 2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience.
• 3+ years of commercial software engineering experience.
• Master in quantitative field (e.g. mathematics, statistics, computer science, EE, etc.), and/or Life Sciences degree with significant computational experience, or equivalent, with 5+ year working experience in Data Science. PhD a plus.
• Experience with LLM applications development including tool using and reasoning, for instance RAG solution and code interpreter.
• Experience with LLM fine tuning a big plus.
• Experience in building data pipelines and deployment pipelines for LLM applications
• Recent experience with ML/AI toolkits such as AWS Sagemager (other toolkits like Pytorch, Tensorflow, Keras, MXNet, H20, etc are nice to have).
• Experience with MLOps technologies (Sagemaker, Vertex AI, Kubeflow).
• Experience with deployment of scalable apps a plus.
  Experience with clinical study data a plus.
• Experience with cloud solutions (AWS / Azure / GCP), docker.
• Proven scripting and automation skills.
• Good knowledge of: git, bash, linux, CI/CD tools (e.g. jenkins, gitlab CI), software lifecycle, RDB, visualization tools eg Tableau, Jira, confluence.
• Programming : Python, R.
• Test driven development, good coding practices.
• Problem-solving and decision-making skills.
• Good interpersonal skills.
• Customer & delivery focus.
• Ability to work effectively with team members and virtual teams from different locations and different cultural backgrounds.