Lead Analyst - Data Science - Maximus

Since 1975, Maximus has operated under its founding mission of Helping Government Serve the People, enabling citizens around the globe to successfully engage with their governments at all levels and across a variety of health and human services programs. Maximus delivers innovative business process management and technology solutions that contribute to improved outcomes for citizens and higher levels of productivity, accuracy, accountability, and efficiency of government-sponsored programs. With more than 30,000 employees worldwide, Maximus is a proud partner to government agencies in the United States, Australia, Canada, Saudi Arabia, Singapore, and the United Kingdom. For more information, visit https://www.maximus.com .

MAXIMUS is seeking a Lead Data Science Analyst with a minimum of 7 years of experience to spearhead and direct efforts in operationalizing data science for our Standardized Operations and Analytics group within our Health and Human Services division. This exciting opportunity will involve delivering insights through pioneering analytical practices, which include devising innovative and advanced analytical solutions that will become integral to our core analytical product offerings. The selected candidate will collaborate closely with a cross-functional team to identify and prioritize actionable, high-impact insights related to various aspects of our business processes. A Lead Data Science Analyst is responsible for the entire lifecycle of analytics initiatives, from research and design to implementation and validation, employing machine learning and predictive algorithms to analyze program performance and enhance operational processes. This role will also partake in ongoing process improvement activities, assist with project management, and execute ad-hoc requests as needed. The position is fully remote, with limited travel requirements; however, travel may constitute up to 15% of the time when necessary.

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.

Project Responsibilities:

• Collaborate with stakeholders across the organization to establish and implement ML Ops best practices and processes, ensuring smooth deployment, monitoring, and maintenance of machine learning models and pipelines.
• Provide strategic expertise in ML Ops techniques and technologies to optimize the end-to-end machine learning lifecycle, including data preparation, model training, validation, deployment, and monitoring.
• Lead the design and implementation of scalable and efficient ML infrastructure, including model versioning, artifact management, and reproducibility, to support the development and deployment of machine learning models.
• Define and enforce data governance policies and practices to ensure data quality, integrity, and compliance throughout the ML Ops workflow.
• Drive continuous improvement and automation in ML Ops workflows, leveraging tools and technologies such as containerization, orchestration, CI/CD pipelines, and monitoring systems.
• Provide strategic expertise in machine learning and data mining techniques to identify and apply appropriate methods, including optimization, simulation, regression, decision trees, neural networks, cluster analyses, mixed models, and more.
• Enlarge datasets, enhance data quality, establish automated anomaly detection systems, and resolve issues.
• Balance analysis accuracy with the need for a swift response, employing several types of data, business acumen, and strategic assumptions when data is unavailable.
• Manage third-party relationships to extend data and capabilities when required.
• Possess a clear understanding of statistical applications' uses and limitations, and effectively communicate relevant information to a diverse range of audiences.

Minimum Requirements

Minimum Requirements:
- 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.

Project Required Experience and Skills

• 7+ years of experience in data analysis, with a strong emphasis on deploying and managing machine learning models in production environments
• Excellent understanding of ML Ops best practices, tools, and technologies, including containerization (e.g., Docker), orchestration (e.g., Kubernetes), CI/CD pipelines, and monitoring systems (e.g., Prometheus, Grafana)
• 5+ years of experience working with common data science toolkits, such as R, Weka, Python/NumPy, MatLab, etc.
• Capability to clearly communicate data findings to educate partners, motivate action, and enhance business outcomes

EEO Statement

Active military service members, their spouses, and veteran candidates often embody the core competencies Maximus deems essential, and bring a resiliency and dependability that greatly enhances our workforce. We recognize your unique skills and experiences, and want to provide you with a career path that allows you to continue making a difference for our country. We're proud of our connections to organizations dedicated to serving veterans and their families. If you are transitioning from military to civilian life, have prior service, are a retired veteran or a member of the National Guard or Reserves, or a spouse of an active military service member, we have challenging and rewarding career opportunities available for you. A committed and diverse workforce is our most important resource. Maximus is an Affirmative Action/Equal Opportunity Employer. Maximus provides equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disabled status.

Pay Transparency

Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment. Annual salary is just one component of Maximus's total compensation package. Other rewards may include short- and long-term incentives as well as program-specific awards. Additionally, Maximus provides a variety of benefits to employees, including health insurance coverage, life and disability insurance, a retirement savings plan, paid holidays and paid time off. Compensation ranges may differ based on contract value but will be commensurate with job duties and relevant work experience. An applicant's salary history will not be used in determining compensation. Maximus will comply with regulatory minimum wage rates and exempt salary thresholds in all instances.