Senior Data Scientist - FFPP-8757

Innovative Systems & Solutions | Full time - Onsite

Annapolis Junction, United States | Posted on 03/17/2026

Innovative Systems & Solutions (ISS) works with a wide spectrum of talent to establish an atmosphere that stimulates creativity, constant progress, and achievement. At ISS, you will have the chance to immediately impact government transformation and our clients' missions by offering information solutions and services to Federal and Department of Defense (DoD) customers. Employees at ISS can look forward to exciting career opportunities.

A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense ofdatasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manualdata analysis into automated analytics;

implement prototype algorithms withinproduction frameworks for integration into analyst workflows.

• Producedata visualizations that provide insight into dataset structure andmeaning
• Workwith subject matters experts (SMEs) to identify important information inraw data and develop scripts that extract this information from a varietyof data formats (e.g., SQL tables,structured metadata, network logs)
• IncorporateSME input into feature vectors suitable for analytic development and testing
• Translate customer qualitative analysis process and goals into quantitativeformulations that are coded into software prototypes
• Develop and implement statistical, machine learning, and heuristic techniques tocreate descriptive, predictive, and prescriptive analytics
• Developstatistical tests to make data-driven recommendations and decisions
• Developexperiments to collect data or models to simulate data when required datais unavailable
• Developfeature vectors for input into machine learning algorithms
• Identify the most appropriate algorithm for a given dataset and tune input andmodel parameters
• Evaluate and validate the performance of analytics using standard techniques andmetrics(e.g. cross validation, ROC curves, confusion matrices)
• Overseethe development of individual analytic efforts and guide team in analytic development process
• Guideanalytic development toward solutions that can scale to large datasets
• Partner with software engineers and cloud developers to develop productionanalytics
• Develop and train machine learning systems based on statistical analysis of datacharacteristics to support mission automation

This position requires in-scope poly, within 7 years.

Bachelor's degree from an accredited college or university in a quantitative discipline (e.g.,statistics, mathematics,operations research, engineering or computer science). Five (5) years of experience analyzing datasets and developing analytics, five (5) years of experience programming with data analysis software such as R, Python, SAS, orMATLAB. An additional four (4) years of experience in software development,cloud development, analyzing datasets,or developing descriptive, predictive,and prescriptive analytics can be substituted for aBachelor's degree.

A PhDfrom an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience.

• Programming
  
  Languages:
  
  Proficiency in programming languages such as Python and R iscrucial for data manipulation, analysis, and implementing algorithms.
  
  Python is favored for its simplicity and extensive libraries (likeNumPyand pandas), while R is preferred for statistical analysis and data visualization.
• Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately and making informed decisions. Understandingconcepts like regression analysis, hypothesis testing, and statisticaldistributions is essential.
• Machine Learning:
  Knowledge of machine learning algorithms and frameworks (such asTensorFlow and Scikit-Learn) is vital for building predictive models andautomating decision-making processes.
• Data Wrangling:
  The ability to clean and organize complex datasets is critical.
  
  Data wrangling involves transforming raw data into a usable format, whichis often time-consuming but necessary for effective analysis.
• Database Management:
  Familiarity with SQL and database management systems (likePostgreSQL and MongoDB) is essential for extracting and manipulatingdata stored in relational databases.
• Data Visualization:
  Skills in data visualization tools (such as Tableau and Matplotlib) help communicate findings effectively. Creating charts,graphs, and dashboards is crucial for making data understandable to stakeholders.

salary range provided is a general guideline. ISSI considersseveral factors when…