Data Scientist (SC)

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

DUTIES: Apply analytical methods to improve decision-making across the company’s Supply Chain. Using mathematical modeling, statistical analysis, and mathematical optimization, execute optimal or near-optimal solutions to complex decision-making problems. Develop inventory management procurement strategies that minimize the company’s investment in inventory while achieving or exceeding service-level targets. Refine logistics network strategy to ensure facility locations and store/customer assignments are optimized to minimize variable costs. Assist in developing carrier strategies for small package distribution services, fleet, TL, and LTL carriers, including route optimization modeling. Enhance and implement product profitability/cost-to-serve models to ensure right products are being stocked in the right locations. Apply analytical methods to solve complex, data-driven business problems that will ultimately have a direct impact on the company’s bottom-line. Communicate results to management as needed. Research, design, and implement data models and innovative algorithms to analyze diverse sources of data to realize actionable results. Support all functional areas within the company’s Supply Chain. Position is fixed location based in Framingham office; however, telecommuting from a home office may also be allowed up to two (2) days per week. Multiple positions available.

Qualifications :

REQUIREMENTS: Requires a Master’sa degree (or foreign equivalent) in Industrial Engineering, Mechanical Engineering, Operations Research, Statistics, or a related field plus two (2) years of industry experience. Experience must include:

Two (2) years of experience in each of the following (experience may be gained concurrently):

• Data mining, mathematical modeling, statistical analysis, and mathematical optimization tools, including linear programming, integer programming, mixed-integer programming, Markov decision processes, and multivariate analysis
• Communicating complex quantitative analysis in a clear, precise, and actionable manner with both technical and nontechnical customers
• Developing applications in NodeJS, Go, Python, Java, or Scala
• Using major statistical analysis tools, such as R, Matlab, or SAS
• Working with RDBMS and NoSQL data stores on-premise and in the Cloud
• Data visualization and BI tools such as Tableau, Power BI, MicroStrategy, or QlikView
• Programming using Python and SQL
• Building dashboards using Power BI or Tableau

One (1) year of experience in each of the following (experience may be gained concurrently):

• Understanding of business domain
• Building solutions on public cloud platforms, such as Azure, AWS, GCP, or Snowflake; using platform services; and integrating with various on-premise systems
• Performing statistical analysis, machine learning, or other algorithm development

40 hours/week. Monday-Friday, 9:00 am – 5:00 pm.