SFL Scientific is expanding our data science consulting team and we are seeking senior and lead data scientists to design and build end to end approaches and ML/AI solutions across healthcare, life sciences, manufacturing, medical devices, and other industries.
Work on complex and R&D type data science problems with organizations of all sizes and across industries. Work with other data scientists, data engineers, architects, and strategists to help detect cancer, understand population health, detect emotion and extract unstructured text meaning, predict crop yields and save resources, detect defects in infrastructure and equipment, predict failures in electrical systems, and sometimes take it a little lighter and predict the best player line-ups on major sports teams. Being a data scientist allows you to be a consultant at SFL Scientific, helping clients solve problems with data first and foremost and work on many varied and skill-expanding projects throughout the year.
The successful candidate will have demonstrated ability to manage projects, provide thought leadership, and act as an autonomous member of the SFL Scientific team. The role of the Senior Data Scientist will include the entire workflow of a data science project: From ensuring data quality throughout all stages of acquisition and processing to the cleaning, visualizing, analyzing, predicting with the data, and creation of a final product or pipeline.
This is a full-time position in Boston, MA. Flexible work schedule and minimal (less than 5%) travel to clients on-site.
Master’s degree in a relevant field
5+ years experience with various data analysis and visualization tools
Proficient in traditional ML and deep learning techniques
Proficient in core programming languages, such as: Python, R, C/C++, Scala and aux sets/tools
Working knowledge of Keras, Tensorflow, PyTorch, Docker, Kubernetes, etc.
Proficient with SQL and NoSQL
Proficient with Tableau, R-Shiny, or other data visualization tools
Proficient with AWS or Azure cloud computing environments
Proficient with a distributed computing platform (Hadoop, Spark, etc.)
Experience querying and administering big data storage services (Redshift, Teradata, Aurora, DynamoDB, etc.)
Experience with general software release cycle, productionizing ML or predictive analytics models at scale.
Base salary, performance bonus/compensation, medical coverage, 401k plan, paid time off (vacation, personal/sick, parental, etc.), flexible work-schedule, on-going industry training, and other company-wide perks.