Data Scientist

Clarity InnovationsTampa, FL

About The Position

Clarity Innovations is a trusted national security partner, dedicated to safeguarding our nation’s interests and delivering innovative solutions that empower the Intelligence Community (IC) and Department of Defense (DoD) to transform data into actionable intelligence, ensuring mission success in an evolving world. Our mission-first software and data engineering platform modernizes data operations, utilizing advanced workflows, CI/CD, and secure DevSecOps practices. We focus on challenges in Information Warfare, Cyber Operations, Operational Security, and Data Structuring, enabling end-to-end solutions that drive operational impact. We are committed to delivering cutting-edge tools and capabilities that address the most complex national security challenges, empowering our partners to stay ahead of emerging threats and ensuring the success of their critical missions. At Clarity, we are people-focused and set on being a destination employer for top talent, offering an environment where innovation thrives, careers grow, and individuals are valued. Join us as we continue to lead innovation and tackle the most pressing challenges in national security. Role This role is for a Data Scientist on a close-knit team supporting a U.S. Special Operations Command program at MacDill AFB. This team is at the center of helping the command empower and leverage its data for more effective analysis and decision making. As a subject matter expert, the Data Scientist will leverage their experience to gather and derive insights from complex data, assist the command with development initiatives, and facilitate digital transformation efforts. The work done in this role has a direct impact on mission readiness as the team's efforts go toward making a more resilient and data-driven organization.

Requirements

  • A minimum of 1 year of hands-on Data Science experience is required.
  • Bachelor's Degree in a STEM field is required.
  • Proficient with one or more programming languages (Java, C++, Python, R, etc.)
  • Proficient in Agile Development and Git operations
  • A Top Secret Clearance with SCI eligibility is required
  • Demonstrated ability to work in a fast-paced environment with evolving requirements

Nice To Haves

  • Familiarity with DoD
  • Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.

Responsibilities

  • Interpret and analyze data using exploratory mathematic and statistical techniques based on the scientific method.
  • Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data
  • Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
  • Coordinate with Data Engineers to build Data environments providing data identified by other data professionals
  • Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
  • Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
  • Design and automate processes to facilitate the manipulation and analysis of data. Manage and integrate data across dissimilar data sets. Analyze large-scale structured and unstructured data.
  • Use frameworks such as Spark and Hadoop to conduct large-scale data processing. Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny.
  • Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages.
  • Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.
  • Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling.
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