Data Scientist II (Remote)

Maximus

15h•$115,175 - $159,125•Remote

About The Position

The Data Scientist II supports the United States Special Operations Command Preservation of the Force and Family (USSOCOM POTFF) program by identifying and implementing innovative, high-value solutions across the Special Operations Forces enterprise. The role applies advanced analytics and research methods to help improve the short- and long-term well-being of SOF service members and their families. The position is remote, is pending contract award, and requires U.S. citizenship and an active Secret clearance or eligibility to obtain and maintain one as required for contract performance. The role combines hands-on data analysis, modeling, data engineering, machine learning, research, and program evaluation. The Data Scientist discovers and prepares data sources, develops features and predictive models, performs statistical analyses and experiments, and communicates mission-relevant findings through dashboards, reports, presentations, and other narratives. The position collaborates with product and technical partners as well as POTFF staff, supported units, and the Government’s POTFF biostatistician. The posting lists qualifications for both POTFF research and analytics duties and technical machine-learning and data-engineering work. Minimum qualifications include graduate-level quantitative or related education, research experience, proficiency with statistical tools and programming, and experience with machine-learning frameworks, big-data architectures, and cloud platforms. A separate minimum-requirements section also lists a bachelor’s degree in a technical field as required and an advanced degree as preferred.

Requirements

Master’s degree in quantitative science, social science, or a related discipline.
B.S. or B.A. in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, or a related technical field (also listed as required in the posting).
Three or more years of research experience in an academic, social services, government, healthcare, or laboratory setting.
Five or more years using major machine-learning or deep-learning frameworks and algorithms, including examples such as Scikit-learn, PyTorch, TensorFlow, Keras, CNN, GAN, LSTM, RNN, and XGBoost.
Five or more years of data engineering experience with modern big-data analytics architectures such as Hadoop, SQL, Hive, Spark, or Snowflake on major cloud platforms such as AWS, Azure, or Google Cloud.
Five or more years of programming experience in Python, Scala, or Julia.
Advanced proficiency with Microsoft Office applications, including Word, Excel, and Access.
Advanced proficiency with commonly used statistical software and programming tools, such as SPSS, SAS, Python, and R Shiny.
Demonstrated advanced research proficiency through relevant employment in academia or another environment where research is routinely conducted.
Demonstrated record of scientific publications.
U.S. citizenship and an active Secret clearance, or eligibility to obtain and maintain a Secret clearance as required for contract performance; the posting also states that active Secret clearance is required at minimum.
Ability to read, write, and speak English fluently and clearly to communicate effectively with all personnel.
Excellent verbal, written, interpersonal, and presentation skills, with strong attention to detail.
Demonstrated initiative, interpersonal effectiveness, and cultural awareness when working constructively with individuals from diverse backgrounds.
Demonstrated leadership and self-direction, and willingness to teach others and learn new techniques.
Ability to communicate complex ideas clearly, precisely, and actionably to technical and non-technical partners.

Nice To Haves

Advanced degree in Computer Science, Information Systems, Business Analytics, Mathematics, Statistics, Engineering, Business Administration, or a related field.
Experience deploying machine-learning models into discovery or production environments using MLOps.
Experience working in an agile delivery model.
Power BI experience.
Doctoral degree in quantitative science, social science, or a related discipline.
Certification or documented experience in human performance.
Experience supporting Special Operations, athletics or sports programs, or other military environments.
Strong capabilities in data visualization tools such as Power BI or Tableau; SQL querying and database management; business analytics and reporting; predictive modeling and forecasting; and dashboard development.

Responsibilities

Perform hands-on analysis and modeling using large data sets.
Apply data mining, natural language processing, and supervised and unsupervised machine learning to improve relevance and personalization algorithms.
Collaborate with product managers, software engineers, and designers to design experiments and minimum viable products.
Identify data sources, obtain access, import and clean data, and prepare it for modeling.
Create and refine features from underlying data.
Conduct regular A/B tests, collect data, perform statistical analysis, assess optimization impacts, and communicate results to peers and leaders.
Explore emerging design and technology changes and assess how they could support customer benefits.
Conduct advanced data analytics, data manipulation, data mining, exploratory analysis, predictive analysis, and statistical analysis.
Translate and correlate data into graphical, written, visual, and verbal narratives that support informed decision-making.
Enter, maintain, and analyze data within government systems.
Develop and maintain dashboards that automate analysis and identify, interpret, and present trends in POTFF program data.
Assist POTFF staff with survey design and with creating, analyzing, and reporting survey results.
Advise supported units and POTFF staff on opportunities and methods for capturing data related to POTFF programs and initiatives.
Collaborate with POTFF program staff and the Government’s POTFF biostatistician.
Provide subject matter expertise in program evaluation, research methodologies, and data analysis.
Use statistical modeling and data visualization to identify trends, outliers, and patterns, and produce reports and presentations communicating mission-relevant findings accurately.
Deploy machine-learning models into discovery or production environments to drive insights, where applicable.

Benefits

Flexible work/life balance support.
Medical, dental, vision, and prescription plans, plus a partially funded HSA.
Life insurance and discounts on auto, home, renters, and pet insurance.
401(k) retirement savings plan with company match.
PTO, paid holidays, extended sick leave, and short- and long-term disability coverage.
Employee Assistance Program (EAP) resources supporting physical, emotional, and financial well-being.
Employee recognition platform.
Tuition reimbursement opportunities.
Employee discounts and additional employee-only benefits.
Wellness programs and resources.
Training programs, workshops, conferences, and ongoing learning opportunities.
Coverage of costs associated with renewing required licenses and certifications.