Senior Data Scientist - Remote, ML & Analytics Expert

MAXIMUS; Milwaukee (WI); Remote; USD 153,000 - 182,000; Full time

Job summary

MAXIMUS is seeking an experienced data science professional to interpret results, build classifiers, and guide analytics strategy. You will act as a subject matter expert, select appropriate techniques, and expand data collection to support robust systems.

The role requires leadership, strong communication, and deep knowledge of ML methods and statistics. Responsibilities include automating anomaly detection, monitoring model performance, and collaborating with business users to drive

Qualifications

• Bachelor's Degree or equivalent experience with 7+ years in data analysis/science.
• Advanced machine learning knowledge: k-NN, Naive Bayes, SVM, Decision Trees, etc.
• Experience with data visualization tools and SQL-driven analytics.
• Strong communication skills with business users and stakeholders.
• Experience leading projects and prioritizing data analysis solutions.

Responsibilities

• Interpret results using data aggregation, statistics, and data mining.
• Select features and refine classifiers using modern ML techniques.
• Act as SME in data and analytics for peers and stakeholders.
• Identify suitable analytical techniques for different frameworks (e.g., optimization, simulation).
• Develop automated anomaly detection and monitor model performance.
• Expand data collection to support robust analytical systems.
• Lead project management activities and coordinate team communication.

Skills

Machine Learning

Statistics

SQL

Data Visualization

Leadership

Communication

Education

BS/MS/PhD in Statistics/Mathematics/OR/CS

Tools

Data Science Toolkits (e.g., scikit-learn, TensorFlow)

Job description

MAXIMUS is seeking an experienced data science professional to interpret results, build classifiers, and guide analytics strategy. You will act as a subject matter expert, select appropriate techniques, and expand data collection to support robust systems.

The role requires leadership, strong communication, and deep knowledge of ML methods and statistics. Responsibilities include automating anomaly detection, monitoring model performance, and collaborating with business users to drive