Description & Requirements We now have an exciting opportunity for a Lead Data Scientist specializing in Algorithm Architectures to join the Maximus AI Accelerator supporting the enterprise at large. We are looking for an accomplished hands-on technical leader and team player to be a part of the AI Accelerator team. You will be responsible for architecting and optimizing scalable, secure AI systems and integrating AI models in production using MLOps best practices, ensuring systems are resilient, compliant, and efficient. Additionally, you will be responsible for developing new and innovative algorithms that further the responsible us of AI at Maximus and enable the business to make data driven decisions by crafting mathematically rigorous decision methodologies. This role requires strong systems thinking, problem-solving abilities, mathematical modeling, and the capacity to manage risk and change in complex environments. Success depends on cross-functional collaboration, strategic communication, and adaptability in fast-paced, evolving technology landscapes. This position will be focused on strategic company-wide initiatives but will play a role in project delivery and capture solutioning (i.e., leaning in on existing or future projects and providing solutioning to capture new work) in addition to managing and expanding our AI Accelerator portfolio and capabilities. Essential Duties and Responsibilities: - Lead, develop, collaborate, and advance the applied and responsible use of AI, ML, mathematical, and data science solutions throughout the enterprise by finding the right fit of tools, technologies, methodologies, processes, and automation to enable effective and efficient solutions for each unique situation. Lead the use of applied mathematical analyses to provide solutions. - Lead efforts across the enterprise to support the creation of solutions and real mission outcomes, emphasizing and teaching the ability to flex and demonstrate initiative when dealing with ambiguous and fast-paced situations. - Act as technical translator and role model for effectively articulating and translating technical needs, solutions, outputs, and impacts to all levels, regardless of technical proficiency, in a respectful, collaborative, and situationally appropriate manner. - Maintain deep, current knowledge of the AI technology landscape and emerging developments, evaluating their applicability for use in production/operational environments. - Lead the creation, curation, and promotion of playbooks, best practices, lessons learned, and firm intellectual capital. What You Will Do: - Lead, develop, collaborate, and advance the applied and responsible use of AI, ML, mathematical, and data science solutions throughout the enterprise by finding the right fit of tools, technologies, methodologies, processes, and automation to enable effective and efficient solutions for each unique situation. Lead the use of applied mathematical analyses to provide solutions. - Lead efforts across the enterprise to support the creation of solutions and real mission outcomes, emphasizing and teaching the ability to flex and demonstrate initiative when dealing with ambiguous and fast-paced situations. - Act as technical translator and role model for effectively articulating and translating technical needs, solutions, outputs, and impacts to all levels, regardless of technical proficiency, in a respectful, collaborative, and situationally appropriate manner. - Maintain deep, current knowledge of the AI technology landscape and emerging developments, evaluating their applicability for use in production/operational environments. - Lead the creation, curation, and promotion of playbooks, best practices, lessons learned, and firm intellectual capital. Minimum Requirements: - Demonstrated professional experience across the following mathematical domains: Calculus, Statistics, Numerical Analysis, & Linear Algebra - Experience in Computer Vision and Natural Language Processing. - Python Experience with TensorFlow, PyTorch, and Pandas Minimum Education requirement: - PhD in Mathematics or Masters in a STEM discipline (e.g. Math, Physics, Engineering) with 3+ publications on AI Algorithms in referred journals Years of Required Work-Related Experience: - 3+ yrs experience in Artificial Intelligence and Machine Learning - 3+ yrs experience in evaluating and proposing AI/ML approaches and solutions associated with mission problem scenarios (to include use of vendor solutions/hardware, open source, and custom development) - 3+ years of programming experience - 3+ years of statistics experience Required Certifications: - None Minimum Requirements - Bachelor's degree in relevant field of study and 7+ years of relevant professional experience required, or equivalent combination of education and experience. Preferred Key Skills and Abilities (not contractually required): - Experience developing signal processing algorithms: - Ability to leverage mathematical principles to model new and novel behaviors. - Ability to leverage statistics to identify true signals from noise or clutter - Experience working as an individual contributor in AI - Use of state-of-the-art technology to solve operational problems in AI and Machine Learning. - Strong knowledge of data structures, common computing infrastructures/paradigms (stand alone and cloud), and software engineering principles - Ability to design custom solutions in the AI and Advanced Analytics sphere for customers. This includes the ability to scope customer needs, identify currently existing technologies, and develop custom software solutions to fill any gaps in available off the shelf solutions. - Ability to build reference implementations of operational AI & Advanced Analytics processing solutions. - Use of a variety of programming languages, including but not limited to Python/Java and frontend frameworks for POC demos and dashboarding - Use and development of program automation, CI/CD, DevSecOps, and Agile - Experience with deep learning model architecture development and philosophy - Cloud certifications (AWS, Azure, or GCP) - 7+ yrs of related experience in AI, advanced analytics, computer science, or software development. EEO Statement Maximus is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics. 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. Minimum Salary $ 151,760.00 Maximum Salary $ 200,000.00 • About the Company: Maximus MAXIMUS provides business services to help governments operate health and human services programs, mostly at the state and national levels. The company's health services segment offers outsourced program management and administrative services, Company Size: 5,000 to 9,999 employees Industry: Healthcare Services Founded: 0 Website: https://www.maximus.com/
Job Type
Fulltime role
Skills required
Python, Azure
Location
Montgomery, Alabama
Salary
No salary information was found.
Date Posted
June 12, 2025
Maximus is seeking a Lead Data Scientist specializing in Algorithm Architectures to optimize AI systems and integrate models using MLOps best practices. This role involves developing innovative algorithms and collaborating across the enterprise to drive data-driven decision-making.