Data Scientist (TS/SCI req'd)

Command Holdings•Tampa, FL

22h•Onsite

About The Position

WWC Global is seeking Data Scientists to support USSOCOM's mission to transform the SOF Enterprise into a decisive data-centric organization. This role involves applying scientific methods, algorithms, processes, and systems to extract actionable insights and knowledge from structured and unstructured data. The Data Scientist will design, implement, and maintain data pipelines, interpret and analyze complex data sets, and manage machine learning (ML) projects using cloud-native platforms and advanced ML solutions. The position requires a TS/SCI clearance and is contingent on contract award. WWC Global is a tribally-owned firm providing management consulting services to U.S. government agencies, with a commitment to equal employment opportunity and providing reasonable accommodations.

Requirements

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Applied Mathematics, or a closely related quantitative discipline.
Current, active TS/SCI security clearance.
A minimum of three (3) years of hands-on experience in data science, machine learning, or a closely related analytical discipline.
Demonstrated experience designing, implementing, and maintaining data pipelines, and interpreting and analyzing complex structured and unstructured data sets.
Demonstrated proficiency in distributed SQL programming, relational and nonrelational data queries, and general programming languages such as Python and R.
Demonstrated experience with machine learning techniques, statistical modeling, and data visualization tools.
Outstanding communication skills, influencing abilities, and client focus.
Professional proficiency in English is required.
Demonstrated proficiency in using all Microsoft Office applications.
Ability to access federal facilities in compliance with Real ID.
Applicants must be currently authorized to work in the United States on a full-time basis.
WWC Global will not sponsor applicants for work visas for this position.

Nice To Haves

Master's degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
Graduate-level coursework in machine learning, artificial intelligence, natural language processing, or statistical modeling.
Five (5) or more years of experience in data science or applied analytics.
Experience supporting Department of Defense (DoD) or Intelligence Community (IC) programs, particularly within the SOF Enterprise or USSOCOM.
Experience working with cloud-based data management and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, or Snowflake.
Experience with big data processing frameworks such as Apache Spark, Kafka, or Hadoop, and containerization technologies such as Kubernetes or Docker.
Experience developing and deploying LLM and Retrieval-Augmented Generation (RAG) solutions.
Experience conducting AI/ML modeling and simulation efforts in support of operational or warfighting use cases.
Experience working in classified environments such as SIPRNet or JWICS.

Responsibilities

Collects, cleans, and prepares data, and applies AI/ML algorithms and visualization capabilities to enable problem-solving across the SOF Enterprise.
Coordinates research and analytic activities utilizing various data points, both unstructured and structured, and employs programming to clean, massage, and organize the data.
Experiments against data points, provides information based on experiment results, and provides previously undiscovered solutions to command data challenges.
Applies scientific methods, algorithms, processes, and visualization capabilities to extract actionable insights and knowledge from structured and unstructured data and uses and seamlessly integrates data into existing analytic tools.
Develops methods to consume and integrate data from various operational platforms to enable near real-time analysis of operational situations and support command decision-making.
Develops predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
Develops AI/ML algorithms and models, including those designed for NLP, Computer Vision, Large Language Models (LLMs), and decision-making, that learn from data to identify patterns and improve performance over time.
Conducts AI/ML modeling and simulation efforts to create models that analyze data, recognize patterns, and make predictions, and uses those models to simulate real-world scenarios to test various outcomes without real-world risks.
Designs and automates processes to facilitate the manipulation and analysis of data, manages and integrates data across dissimilar data sets, and analyzes large-scale structured and unstructured data.
Uses frameworks such as Spark and Hadoop to conduct large-scale data processing, and performs 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.
Designs and tests analytics and AI-enabled solutions side-by-side with stakeholders, including business users and warfighters, and demonstrates capabilities via robust campaigns of learning.
Performs statistical modeling and creates data visualizations using products like Tableau, Microsoft Power BI, and R Shiny, and communicates complex concepts and hypotheses to a non-technical audience through digital storytelling.
Adheres to Integrated Governance Standards by supporting the Department of War's integrated data, analytics, and AI governance approach, and ensures data compliance and trust by aligning all data and analytics products with SOCOM security and data strategies.
Develops and delivers unique analytic custom solutions where existing commercial or Government tools are insufficient, including executable code scripts, enterprise dashboards, visualizations, web applications, or full-stack applications, incorporating innovative technologies such as AI, ML, RPA, NLP, and Topic Modeling.