Senior Data Scientist (Active TS/SCI Clearance)

“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” — Dr. Jim Rebesco, Cofounder and CEO, Striveworks The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it. Striveworks was built to solve that problem. What you’ll build Since 2018, we have delivered the most trusted AI systems operating in real-world use cases—providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab. As a Senior Data Scientist at Striveworks, you will be a core contributor to the projects, products, and direction of the company. Working as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers, you’ll develop and validate machine learning models and custom analytic algorithms applied to image, video, text, geospatial, time series, and structured data. You will also implement AI-based software solutions for cloud and edge environments. What it’s like here We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice. What we’re looking for A BS degree in computer science, machine learning, mathematics, or a related discipline and 6+ years of relevant experience Proficiency in machine learning and data science, and applying both to image and video data Proficiency in implementing and analyzing data structures and algorithms Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn Experience developing anomaly detection algorithms for AI systems, models, data, and workflows Exposure to software development life cycles and tools (e.g., Git, Agile) Active TS/SCI security clearance and US citizenship, as well as eligibility and willingness to undergo a Counterintelligence (CI) Scope Polygraph if required The following isn’t required, but we’d love to see it: An advanced degree in computer science, machine learning, mathematics, or a related discipline Experience deploying machine learning and data science solutions to production environments Exposure to DevOps and cloud infrastructure (e.g., Docker, K8s, and CI/CD) Experience processing unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF,…