About TaskUs: TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies, helping its clients represent, protect and grow their brands. Leveraging a cloud-based infrastructure, TaskUs serves clients in the fastest-growing sectors, including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech. The People First culture at TaskUs has enabled the company to expand its workforce to approximately 45,000 employees globally.Presently, we have a presence in twenty-three locations across twelve countries, which include the Philippines, India, and the United States. It started with one ridiculously good idea to create a different breed of Business Processing Outsourcing (BPO)! We at TaskUs understand that achieving growth for our partners requires a culture of constant motion, exploring new technologies, being ready to handle any challenge at a moment’s notice, and mastering consistency in an ever-changing world. What We Offer: At TaskUs, we prioritize our employees' well-being by offering competitive industry salaries and comprehensive benefits packages. Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity. We take pride in our inclusive environment and positive impact on the community. Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs. Join our team today and experience firsthand our dedication to supporting People First. Why this role exists Our researchers invent safety methods and our delivery teams deploy them but we need data to prove they work, fast. You’ll bring statistical rigor and analytical firepower to every benchmark, red‑team, and client rollout. Your models, dashboards, and experiments will show customers where their risks lie and how our interventions move the needle. The impact you’ll make Quantify safety: Transform evaluation outputs into clear metrics, confidence intervals, and risk scores that guide client decisions. Accelerate research: Provide rapid statistical feedback that helps researchers iterate on alignment, robustness, and interpretability ideas. Strengthen delivery: Build data pipelines and visualizations that give Solutions and Operations teams real‑time visibility into project health. What you’ll do Own analytics pipelines for jailbreak detection rates, toxicity scores, drift signals, and other safety KPIs—ETL through presentation. Design A/B and sequential tests to measure the impact of prompt tweaks, fine‑tuning, or policy changes on model behavior. Develop risk models & dashboards in Python (Pandas, NumPy, Plotly, Streamlit) backed by scalable storage (BigQuery, Redshift, or similar). Collaborate with Researchers to choose statistical methods, validate assumptions, and publish reproducible notebooks alongside papers. Partner with Solutions Engineering to embed metrics in client reports and scope data requirements for new engagements. Automate reporting: Build CI hooks or Airflow jobs so safety scores refresh with each new model drop or data batch. Stay current: Evaluate new safety benchmarks, open‑source metric libraries, and MLOps best practices; recommend adoption where useful. Experiences you’ll bring 3–5 years in data science, analytics engineering, or applied statistics—ideally in an AI/ML or risk domain. Proven track record turning messy, high‑volume data into actionable insights and visualizations for stakeholders. Solid understanding of machine‑learning evaluation workflows; exposure to large language model outputs a plus. Hands-on experience with Python data stack (Pandas, NumPy, SciPy, scikit‑learn) and SQL—or equivalents in Spark/BigQuery. Familiarity with experiment design, hypothesis testing, and causal inference techniques. Core skills you'll need Statistical rigor: power analysis, significance testing, bootstrap / Bayesian methods. Data engineering basics: ETL, data validation, versioning, and scalable storage. Visualization & storytelling: interactive dashboards and clear narratives for technical & executive audiences. Scripting & automation: write maintainable code, schedule pipelines, and integrate with CI/CD. Collaboration: work fluidly with researchers, engineers, and clients‑facing teams under tight timelines. Nice to have: Experience with MLflow or Weights & Biases, exposure to privacy‑preserving analytics, or familiarity with NIST RMF / EU AI Act metrics. Why you’ll love this role Work remote Immediate impact: Your analyses steer decisions for frontier AI deployments weeks after you write them. Breadth of problems: From toxicity scoring to drift detection, no two problems are the same. Growth runway: Define the data science discipline for AI Safety at TaskUs and grow into a senior or lead role as the team scales. Mission focus: Help ensure the world’s most powerful models behave safely and fairly. How We Partner To Protect You: TaskUs will neither solicit money from you during your application process nor require any form of payment in order to proceed with your application. Kindly ensure that you are always in communication with only authorized recruiters of TaskUs. DEI: In TaskUs we believe that innovation and higher performance are brought by people from all walks of life. We welcome applicants of different backgrounds, demographics, and circumstances. Inclusive and equitable practices are our responsibility as a business. TaskUs is committed to providing equal access to opportunities. If you need reasonable accommodations in any part of the hiring process, please let us know. We invite you to explore all TaskUs career opportunities and apply through the provided URL .