Senior AI Data Scientist

Key Skills

Aartificial intelligence, Algorithms, AWS Sagemaker, ChatGPT, Data science techniques, Effective communication skills, Employee life cycle, Large Language Models - LLMs, Machine learning techniques, MLflow, Presentation skills, SDLC, SQL, Statistics

Job Description

The Vision 

PLS envisions becoming the life sciences investment industry's best tech-enabled investment platform. The AI (Artificial Intelligence) team aims to provide best-in-class intelligence support across all steps of the investment process, from deal sourcing to exit. The system will function as an additional team member and help augment the investment team to make better investments and build better companies for unmet therapeutic needs. Ultimately, PLS will become a scientifically driven investor across the life science ecosystem from academic spinouts to venture rounds and to exit. Come be part of our vision! 

The Role 

As a PLS senior AI Data Scientist, you will be a key member of our new global Data and Artificial Intelligence team. This team’s goal is to build state-of-the-art data and AI technologies and products with strong research fundamentals for our life sciences investment arm. You will utilize your deep expertise in the data sciences and engineering to investigate and build data sources, models, and AI products that support the investment process. These models and AI products include disease mapping, portfolio management predictions, financial planning, and operational streamlining and optimizations. This is a great opportunity to lead on a range of AI powered products in a growing team with exposure to the best life science companies today. 

Responsibilities 

• Establish and evolve our AI model development process for several life sciences investment AI based products at PLS 

• Work with researchers, other data scientists, software engineers, and investors to develop and improve an AI and analytics platform which can support our investments team 
• Lead the research and development on AI algorithms and models at PLS, keeping abreast of the latest developments in the AI space 
• Take an innovative approach in the use, evaluation, and development (where needed) of state of the art or novel models and technologies relevant to our products

• Including Generative models (e.g. Large Language Models (LLMs)) as well as more classic ML and NLP models 
• Some emphasis on the evaluation and shaping of Generative models for our use-cases 

• Mapping, fusion, and feature engineering of multiple complex data sets including biological, medical, financial, corporate, others to be used as input for ML/AI models. 

• Data sources within biological and financial data sources including but not limited to PubMed, Patents, SEC (Securities and Exchange Commission) filing, other biological databases, financial data sets, and others 

• Collaborate closely with different functions to evangelize an AI supported investment process 
• Optimization and streamlining of operational work such as talent management, deal structuring, portfolio management with data solutions and AI models
• Benchmark, evaluate, and document model performance, and provide recommendations for continuous improvement of models 

Requirements 

• Master’s degree or PhD in computer science, artificial intelligence, applied mathematics, statistics, machine learning or related discipline 
• 5-7 years of applied experience in machine learning, deep learning methods, statistical data analysis and complex data visualization; experience in life science industry would be a plus 
• Deep experience with Python

• Design and implement AI solutions working within a Software Engineering Life Cycle (SDLC (Software Development Life Cycle)) 
• Experience with the more recent large language models (GPT-4, Stable Diffusion models, others, other more focused language models) 
• Experience or strong interest in working with cloud computing systems (preferably AWS (Amazon Web Services)) 
• Experience with AI platforms such as SageMaker, MLFlow, others, preferred 
• Experience with building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, Keras, Scikit learn etc. 

• Knowledge of relational database architecture and data management with expertise in SQL 
• Familiarity with software development practices such as unit testing, code reviews, and version control 
• Excellent analytical skills and presentation skills
• Strong verbal and written communication skills and ability to work independently and cooperatively 
• Proficiency in English 

• US Work Visa - Will not require employer sponsorship now or in the future
• Salary range $170,000-$240,000+ DOE + 20% bonus
• Hybrid work schedule: Able to be in San Francisco office, in-person at least 3 days per week, option to work from home 2 days per week