{"id":68616,"url":"https://alion.io/job/actif-ai-senior-data-scientist-actif-ai","title":"Senior Data Scientist - Actif.ai","company":{"id":11679,"name":"Actif.ai","domain":"actif.ai","url":"https://alion.io/company/actif-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":90000,"max_usd":202000,"period":"year","method":"global_role_seniority_cell","sample_n":2679},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AI Agents","optional":false},{"name":"bandit","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"SQL","optional":false},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"GCP","optional":true},{"name":"GitHub","optional":true},{"name":"Google BigQuery","optional":true},{"name":"LightGBM","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true}],"status":"live","first_seen_at":"2026-08-21T12:51:18Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-29T23:01:29Z","board_verified":true,"closed_at":null,"days_open":69,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":69},"description":"Actifai is seeking a Senior Data Scientist for a hybrid or remote position.\nThe Company\nActifai is an artificial intelligence company. We help clients - primarily those in the cable and telecom industry - optimize their high-value, high-leverage decisions. Our platform supports real-world decision-making and business processes across acquisition, retention, pricing, and upselling by combining machine learning, experimentation, reinforcement learning, and emerging agentic orchestration.\nActifai was created by Foundry.ai, a technology fund/studio that builds AI software companies in partnership with large global enterprises. Foundry’s operating companies focus on practical applications of AI that drive immediate, measurable, and recurring improvements to financial performance. Foundry is backed by approximately $100MM in capital from leading private equity and venture capital partners.\nActifai was among the first to bring AI to telecommunications companies at scale. As of 2026, it works with over 35 ISPs across North America and the UK, making it a leading provider of AI sales and support technology to the sector.\nThe Position\nWe are seeking a Senior Data Scientist to join our team. In this role, you will help envision, design, code, test, and improve the models and algorithms at the core of our business. This role goes beyond building predictive models, you will help define what should be built, measured, how decisions are evaluated, and how learning systems evolve in production.\nYou will work across modeling, experimentation, and reinforcement-learning-driven decisioning, partnering closely with engineering and product teams to translate data into reliable, high-impact behavior in live applications. As Actifai expands into agent-style decision systems, you will help support the modeling, evaluation, and learning components that inform those systems.\nSuccessful candidates are comfortable operating with autonomy, framing sometimes ambiguous business problems, validating assumptions through data exploration, and balancing statistical rigor with practical product constraints in a fast-moving environment.\nKey Responsibilities\nFrame and measure decision problems\nTranslate business asks into clearly defined modeling tasks and evaluation frameworks\nPerform exploratory analysis to assess data quality, label stability, and measurement feasibility before modeling\nDefine success metrics, guardrails, and counterfactual approaches\nIdentify sources of bias or limitations introduced by product and operational flows, agent behavior, or data collection\nDevelop predictive models and decision logic\nCreate and maintain training datasets from multiple production data sources\nEngineer and validate features with attention to temporal correctness and leakage\nTrain and evaluate supervised learning models for customer decision problems\nImplement and tune decision logic, including contextual bandit / reinforcement learning approaches layered on predictions\nEvaluate model and policy performance through offline analysis and simulation\nDesign experiments and evaluate impact\nDesign and analyze A/B tests or staged rollouts\nAnalyze experimental outcomes and translate results into product decisions\nDiagnose unexpected results, sample issues, or measurement artifacts\nPartner to operationalize and improve systems\nSpecify model inputs, outputs, and logging requirements needed for monitoring and evaluation\nWork with engineers to integrate models into live workflows\nBuild dashboards to monitor model and decision performance\nInvestigate anomalies and recommend system improvements\nCommunicate findings and tradeoffs to product, engineering, and client stakeholders\nQualifications\nWe are looking for candidates who bring strong applied judgment along with technical depth:\n4+ years of experience in applied data science or machine learning\nStrong Python and SQL skills. Comfortable working with large, messy real-world datasets\nExperience developing and evaluating supervised ML models\nPractical experience with experimentation and statistical reasoning\nFamiliarity with reinforcement learning or decisioning frameworks\nDemonstrated ability to independently frame problems and drive analysis from ambiguity to impact\nStrong communication skills across technical and business audiences\nNice to Have:\nExperience in telecom, subscription, pricing, churn, or retention analytics\nExposure to contextual bandits, RL, or policy optimization\nExperience working in multi-client or product-driven analytics settings\nFamiliarity with AI agents\nEducation\nDegree in a STEM discipline preferred (or equivalent practical experience)\nTools and Technologies\nOur team frequently uses:\nPython, SQL\nGitHub, Google Cloud\nLightGBM, Scikit Learn, PyTorch\nDocker, Bokeh, BigQuery, FastAPI\nBenefits and Culture\nActifai offers an extremely competitive compensation package, including:\nCompany equity grants.\nEmployer-covered health, vision, and dental insurance (with an optional FSA).\n401k matching.\n20 days of PTO allowance per year, with unlimited carryover, and 10 annual holidays.\nEmployees can work either remotely or from our office in downtown Washington, D.C.\nSuccessful candidates will join a small team of ambitious, supportive co-workers with ample opportunities to take on responsibilities beyond their assigned role.\nFor additional information on benefits & what it's like to work at Actifai, please visit actif.ai/careers.","description_format":"text","description_chars":5435,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan","Dental insurance","Equity"],"hiring_locations":[{"name":"United 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