Lead Data Scientist

Overview

Ledelsea Greater Minneapolis-St. Paul Area

Ledelsea Greater Minneapolis-St. Paul Area

The scope of the role includes all facets of company financial performance via delivering data driven solutions that uncover insights that enable optimization. This role is an enterprise position that will support all functions and lines of business within the organization and requires the ability to quickly come up to speed on new business domains, supporting functions and a variety of technology tools that can vary by domain or function.

The role requires continuing to shift skillsets to keep up with an increasingly dynamic business and changing technology landscape.

About the Role

MUST BE LOCAL

Contract to Hire

Hybrid

Schedule:

On-site 3 days a week (Tuesday, Wednesday and Thursday)

Machine learning, predictive modeling analysis (45-55%)

• Implement supervised and unsupervised machine learning algorithms, including regression, tree-based models, clustering, NLP, etc.
• Translate business requirements into technical specifications required for applying machine learning techniques.
• Implement machine learning techniques using modern analytic environments in Python and/or R.
• Research machine learning and AI techniques and technical proofs-of-concept to ensure optimal solutions.
• Leverage technologies such as Python, R, Docker, scripting, etc. to develop and deploy production-ready scripts for ongoing model scoring and training as appropriate.

Exploratory Data Analysis (25-35%)

• Perform data manipulation and munging, including data cleansing, transformations, integrations, missing value imputation, etc.
• Identify data sources appropriate to solve business problems, requiring expertise in data manipulation for data as large as billions of records across dozens of interconnected sources.
• Identify business use cases and specify data sources, analysis techniques, and quantitative outputs.
• Provide quantitative structure to business problems.
• Present results, make recommendations, and explain complicated mathematical ideas in simple terms for business partners.

Data Science Leadership (15-30%)

• Educate stakeholders on data science, analytics, and how it can solve business problems.
• Collaborate with other data scientists in other teams across the organization to brainstorm how to solve business problems.
• Oversee the work of intermediate and associate data scientists and guide them to develop their skills.
• Participate in enterprise-wide initiatives to advance data science maturity.

• Not Applicable

• Full-time

• Science

• IT Services and IT Consulting