• Define and maintain product success metrics and KPI frameworks for key product areas (e.g., quality signals, transparency, outcomes), ensuring clarity, alignment, and consistency across teams. • Build and evolve measurement approaches that connect product changes to business outcomes (funnel metrics, engagement, and revenue impact). • Design and analyze experiments (A/B tests, quasi-experiments) and apply causal inference techniques where randomization isn't feasible. • Develop durable reporting and dashboards that provide ongoing visibility into product health, leading indicators, and strategic goals. • Partner with Product and Engineering to improve instrumentation and event logging, ensuring data is accurate, complete, and decision-ready. • Conduct deep-dive analyses to identify user behavior patterns, friction points, and opportunity areas; translate findings into clear, prioritized recommendations. • Create compelling narratives that synthesize complex analyses into actionable insights for product and business leaders. • Establish lightweight analytics "operating rhythms" (regular readouts, metric reviews, launch measurement plans) to accelerate learning and accountability. • Partner to support survey data governance by analyzing sampling strategies, monitoring and interpreting response trends, and ensuring survey execution aligns with agreed standards.

• Manage and prioritize the backlog (bugs, improvements, and technical debt) • Balance urgent requests with the planned evolution of products • Act as a bridge between Support, Customer Success, Sales, and Engineering • Translate customer needs into clear, actionable requirements • Ensure the quality and stability of deliveries (avoiding regressions) • Monitor product and quality metrics (e.g., SLA, bugs, uptime) • Identify continuous improvement opportunities (quick wins and enhancements) • Communicate the roadmap, progress, and constraints transparently

• Feature Engineering: Go beyond surface-level signals — you'll mine internal and external datasets to engineer high-signal features (DTI, PTI, payment behavior, account balance patterns) that directly improve the predictive power of production credit models. • Model Development: Own the end-to-end development of strategic credit risk models, not just as technical exercises, but as tools that shape how Kafene decides who to approve, for how much, and at what risk. • Data Preparation: Source, clean, and transform messy real-world financial data into modeling-ready datasets. • Vendor Evaluation: Evaluate third-party data vendors and scoring products on their merits, not just their sales pitch. • Research & Innovation: You'll have the latitude to bring in new techniques from the ML literature and apply them to real credit risk problems. • Model Implementation & Validation: Partner with engineering to get your models into production accurately and efficiently. • Monitoring & Maintenance: Stay close to how your models behave in the wild. • Compliance & Governance: Navigate model risk governance, regulatory requirements, and data vendor usage policies with confidence. • Cross-Functional Partnership: Translate business questions from risk, finance, and sales into modeling problems — and explain your solutions back in plain language.

Build, Deploy, and Maintain AI for an Unpredictable WorldStriveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective. With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments. The RoleAs a Senior Data Scientist at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to the projects, products, and direction of the company. You will be a key Striveworks representative and technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will work as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers to transform machine learning models into functional products. You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software and data science to solve real-world problems. You know that being customer focused, rigorous in approach, clear in communication, and able to identify repeatable value opportunities are all critical to success. You are able to sense the needs of the customer, identify evolving demands, and then synthesize that feedback into actionable suggestions for Striveworks’ product teams. Your day-to-day will include: - Working with customers, engineers, and other stakeholders to define clear requirements that solve customers’ problems and leverage the capabilities of our AIOps platform - Developing and validating machine learning models and custom analytic algorithms that are applied to image, video, text, geospatial, time series, and structured data - Orchestrating and automating complex data and analytic pipelines - Implementing AI-based software solutions for cloud and edge environments - Conducting mission-critical field work and interfacing with customers and other stakeholders This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 25% of the time. The Right FitIn addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results. Here’s what we’re looking for: - BS degree in computer science, machine learning, mathematics, or a related discipline and 6+ years of relevant experience - Expertise in machine learning, data science, and their application to image and video data, as well as experience deploying those capabilities to production environments - Expertise in implementing and analyzing algorithms and data structures - 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 - Exposure to DevOps tooling and best practices (e.g., Git, Docker, Kubernetes, CI/CD) - Active Secret (or above) US security clearance - Due to the nature of this role, candidates must have US citizenship The Wish ListWe’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of: - Advanced degree (MA, PhD) in computer science, machine learning, mathematics, or a related discipline - Experience processing a variety of unstructured data types (e.g., imagery, full motion video, text, acoustic, sonar, RF, geospatial, graphs, or telemetry signals) - Experience building AI agents and agentic workflows - Experience implementing ETL pipelines, data pipelines, and/or workflow automation - Experience developing solutions in a compiled programming language (Go, Rust, C++, Java, etc.) - Experience building full-stack applications (back end, front end, REST) or solutions targeted for cloud infrastructure (AWS, Azure, GCP) and/or Kubernetes (K8s) - Experience leading a small team - Experience delivering technology solutions in secure government environments - Experience working with federal, state, and/or local government customers The anticipated base pay range for this position is $170,000–$200,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses. The Benefits - Medical/dental/vision insurance - Voluntary life, long-term disability, accident, and hospital indemnity insurance - HSA and FSA (including dependent care FSA) plans - 401(k) plan - Unlimited PTO - Paid parental leave Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind. If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire. Striveworks is a participating employer in the E-Verify program.