Description & Requirements
Essential Duties and Responsibilities:
- Expertly interpret results using a range of techniques, from basic data aggregation and statistical analysis to advanced data mining and pattern recognition.
- Select crucial features, construct, and refine classifiers using cutting-edge machine learning techniques for enhanced performance
- Act as a subject matter expert (SME) in data and analytics, providing guidance and expertise to peer analysts and operational stakeholders.
- Identify the most suitable decision technology techniques to apply within various analytical frameworks. Examples of decision technology tools that may be employed include optimization, simulation, regression, decision trees, neural networks, cluster analysis, mixed models, and more.
- Utilize appropriate statistical analysis and quantitative methods to thoroughly examine data, forecast future trends, and account for variability, particularly in generating and maintaining reliable predictions
- Expand and refine MAXIMUS data collection procedures to encompass information crucial for building robust analytical systems.
- Develop automated anomaly detection systems and consistently monitor model performance for continuous improvement.
- Lead project management activities and facilitate team communication and strategy implementation (meetings, etc.) to ensure timely and efficient execution.
- Stay abreast of emerging technologies and systems relevant to MAXIMUS initiatives, ensuring the continuous growth of the team's expertise.
- Drive the execution of additional MAXIMUS areas of strategic interest, further enhancing the organization's capabilities and impact.
- Bachelor's Degree or equivalent experience and 7+ Years
- BS, MS (preferred), or PhD in Statistics, Mathematics, Operations Research, Computer Science, - Machine Learning or a related field.
- 7+ years of relevant professional experience in data analysis/science with heavy emphasis on data-driven decision making.
- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Trees, etc.
- Experience with common data science toolkits. Excellence in multiple of these is highly desirable
- Experience with data visualization tools
- Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
- Highly skilled in using query languages such as SQL and expert use of relational databases and SQL
- Experience working with large data sets, experience working with (not architecture design of) distributed or cloud computing tools a plus
- Ability to work independently with minimal supervision or work cooperatively in a technical team as required.
- Must possess superior oral and written communication skills.
- A strong passion for empirical research and for answering complex questions with data.
- Leadership in prioritizing projects and evaluating data analysis solutions
- Experience working directly with business users and requirements documentation
- Experience with solution/vendor evaluation and evaluating product ROI
- Experience with government sponsored health care programs and operations desirable.