Scientific - Data Scientist
: Job Details :

Scientific - Data Scientist Location - Lawrenceville, New Jersey 08648Role is 100% onsite. Junior (0-3 Yrs.) Description Leads discovery and optimization (LDO) is a diverse group of scientists and engineers, providing critical assay information to therapeutic research centers (TRCs) throughout research and early development (R&ED). We are seeking a highly motivated and innovative data scientist to join the data science and advanced analytics team within LDO until the end of 2023. The individual will develop a machine learning and Bayesian statistics-based approach to model assay variability using medium to high throughput screening datasets. The individual will work in a highly dynamic environment at the center of the R&ED drug discovery engine to develop cutting edge tools applied to complex drug discovery problems. Roles and Responsibilities •Write python scripts to enable rapid cleaning and analysis of medium and high throughput datasets •Utilize machine learning (ML) approaches to generate small molecules features •Utilize Bayesian statistics approaches to estimate uncertainties in assay datasets, based on results on above ML outputs •Write and document programming code (python preferred) to facilitate data preparation / cleaning, model development, and evaluation •Produce high quality scripts, documentation, and processing pipeline by the end of 2023 •Create deployable version of processing pipeline for near term use as a stand-alone application and ultimately future integration with enterprise suite Qualifications •Ph.D. in quantitative sciences/engineering (computer science, mathematics, statistics, or engineering) •5+ years of relevant professional experience with a proven track record in machine learning and data science - experience in drug discovery machine learning is desirable but not required •Strong knowledge of one or more scripting programming languages, with a focus on machine learning (e.g., Python (preferred), R, Matlab, C/C++) •Experience utilizing molecular features of small molecules in machine learning models •Experience with the use and application of Bayesian statistics and simulation methods in generating probabilistic outcomes •Able to extract information from databases using a variety of software packages (e.g., Oracle SQL developer) •Ability to build and maintain databases aligned with enterprise solutions is desirable but not required •Strong analytical and problem solving skills to understand technical business problems and implement solutions •Ability to work effectively on matrixed teams to collaboratively solve challenging problems, while also able to work independently with minimal resources •Has good interpersonal, communication, writing and organizational skills •Strong preference for on-site presence to enable colocation with data science team