Senior Data Scientist (Remote) - ML & Data Strategy Lead

MAXIMUS; Minneapolis (MN); Remote; USD 153,000 - 182,000; Full time

Job summary

Maximus is seeking a senior data scientist in the Minneapolis area to interpret complex data, build predictive models, and guide analytic strategy. You will act as a SME for data and analytics, collaborating with analysts and stakeholders to deploy robust decision-support solutions.

The role emphasizes leading ML projects, expanding data collection, and staying current with technologies to increase organizational impact. Strong communication is essential.

Qualifications

• Bachelor's degree or equivalent with 7+ years in data analysis/science.
• Advanced machine learning knowledge and algorithms such as k-NN, SVM, trees.
• Experience with data visualization tools.
• Proficient in SQL and relational databases.
• Able to work independently or in a team and communicate clearly.
• Experience with government sponsored health care programs desirable.

Responsibilities

• Interpret results using data aggregation, statistics, and data mining.
• Select and refine classifiers with ML techniques.
• Act as SME in data and analytics for peers and stakeholders.
• Identify suitable decision technology techniques for analytical frameworks.
• Develop automated anomaly detection and monitor model performance.
• Lead project management and facilitate team communication.
• Stay updated on emerging technologies relevant to MAXIMUS initiatives.
• Drive execution of other MAXIMUS strategic areas.
• Expand data collection procedures for robust analytics.

Skills

Statistical analysis

Machine learning

Data mining

Pattern recognition

SQL

Data visualization

Communication

Leadership

Independent work

Education

BS in Statistics/related field

MS or PhD preferred

Tools

Python

R

TensorFlow

Spark

Job description

Maximus is seeking a senior data scientist in the Minneapolis area to interpret complex data, build predictive models, and guide analytic strategy. You will act as a SME for data and analytics, collaborating with analysts and stakeholders to deploy robust decision-support solutions.

The role emphasizes leading ML projects, expanding data collection, and staying current with technologies to increase organizational impact. Strong communication is essential.