Senior Data Scientist

Senior Data Scientist role

Duration: 6 months – look to convert after this. NO SPONSORSHIP!!

Location: Can sit 100% remote during the contract duration, but since they want to convert this person eventually, there will then be a 3 day / week onsite requirement. Can either sit in Boston/Quincy, MA or Chicago office – MUST BE LOCAL TO THOSE LOCATIONS!!!

IV Process: 2 rounds

UPDATED NOTES!!!!

• Must have over 5 years of experience programming with Python as a Data Scientist
• MUST HAVE RETAIL EXPERINCE (EX: Walmart, Amazon, Target, Lowes, Home Depot)
• Pyspark
• Knowledge of a whole data science project from inception to completion
• Orchestration-- working with docker, CI/CD tools
• Jenkins, terraform
• Huge plus here
• Databricks-- not as important, a nice to have here

Job Description:

This position will involve applying advanced analytics to extract actionable insights from complex datasets, facilitating data-driven decision-making across the organization. The Resource will design and implement predictive models, optimizing business processes

through the development of machine learning algorithms. The focus is on delivering measurable outcomes, enhancing productivity, and improving resource allocation. The lasting impact of these contributions will be the integration of data-driven decision-making

into the ADUSA organizational framework, positioning ADUSA at the forefront of innovation in the industry.

Location: Remote Position

Tasks/Deliverables

• Building the production codebase for the Advanced Analytics models

• Creating training pipelines

• Creating inference pipelines

• Apply advanced analytics for actionable insights

• Implement predictive models with a focus on machine learning for optimization

• Collaborate on data-driven solutions for business challenges

Skills

• Python, Databricks-PySpark framework

• libraries: Prophet, Nixtla, itertools, scitkitlearn, etc

• Data/Training pipeline development, EDA, Feature Engineering, Model delivery, etc.

• Forecasting and Time Series analysis