Kaizen Analytix LLC

Data Scientist

Remote, USPosted 8 days ago

Job Description

Employment Type

: Contract

Location

: Remote

Travel Required

: N/A

About Kaizen

Kaizen Analytix is a global technology consulting firm that helps organizations unlock the full value of their data through advanced analytics, artificial intelligence, and modern data platforms. We partner with clients across industries to solve complex business problems, modernize legacy systems, and drive measurable outcomes. At Kaizen, we combine deep technical expertise with a collaborative, people-first culture focused on continuous improvement. Our teams work at the intersection of strategy, technology, and execution to deliver solutions that make a real impact.

Job Overview

Kaizen Analytix LLC, an analytics services company seeking a qualified Data Science Contractor with a background in exploratory analysis, data modeling, regression analysis, and ML/AI models. The ideal candidate has elasticity estimation and/or pricing experience. Responsibilities and job requirements are below. This role requires a 40-hour/week commitment for 6 months with possible extension.

Key Responsibilities

  • Provide analytical support by leveraging data mining tools and analytical methodologies
  • Assist in data modeling and analysis to determine key customer insights, drive business strategies, and maximize ROI
  • Integrate internal and external data sources, be comfortable working with both structured and unstructured data
  • Assist in development, maintenance, and enhancement of statistical models in Python
  • Use statistical tools and techniques to extract and analyze trends from the customer database warehouse
  • Prepare and deliver presentations with complex analytical concepts
  • Comfortable presenting to the business and upper management

Qualifications

Education and Experience

:* PhD in Operations Research, Econometrics, or other applied mathematical discipline with at least 1 year of relevant professional experience

OR* Master’s degree in

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