{"id":2068327,"url":"https://alion.io/job/exl-sr-data-scientist-causal-modeling-experimentation","title":"Sr. Data Scientist – Causal Modeling & Experimentation","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":81,"open_postings":65,"ghost_share":0,"stale_share":0.954,"repost_share":0,"time_to_fill_p50_days":7,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Jersey City, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":103000,"max_usd":197000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1089},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":true},{"name":"GCP","optional":true},{"name":"Machine Learning","optional":true},{"name":"Python","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-10-07T19:09:31Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T18:42:33Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Senior Data Scientist\nHybrid, NYC\n$100-130k plus bonus\nFor more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits\nThe posted range is the hiring range for this role - a subset of the broader range available to employees over time - and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.\nWe are seeking a highly skilled Sr. Data Scientist with strong expertise in causal inference, experimentation, predictive modeling, and advanced analytics. The role will focus on developing data-driven solutions to understand customer or business behavior, identify incremental impact, optimize targeting strategies, and measure the effectiveness of business interventions.\nThe ideal candidate will have a strong foundation in statistical modeling and experimental design, with the ability to translate complex analytical findings into actionable business recommendations. The role requires experience working with large datasets, developing scalable analytical solutions, and partnering with cross-functional stakeholders to solve complex business problems.\nKey Responsibilities\nApply causal inference methods-including propensity score matching, difference-in-differences, synthetic controls, and randomized or quasi-experimental designs-to quantify business impact\nBuild predictive, uplift, and treatment-effect models to improve targeting, prioritization, and resource allocation\nDesign and analyze A/B tests, including sample sizing, control and treatment groups, statistical testing, and segment-level effects\nAnalyze large datasets, develop reproducible analytical frameworks, and collaborate on scalable data pipelines\nPartner with cross-functional teams and communicate findings, recommendations, and business impact to technical and non-technical stakeholders\nSuccess Measures\nDeliver reliable, scalable models and experiments that quantify incremental impact and improve business decisions\nOptimize targeting and resource allocation through statistically rigorous analysis\nClearly communicate insights and recommendations across business and technical teams\n Required Qualifications\nBachelor’s or Master’s degree in a quantitative field and 4+ years of relevant data science or advanced analytics experience\nStrong knowledge of causal inference, experimental design, statistical testing, regression, sampling, confidence intervals, and power analysis\nHands-on experience with predictive, uplift, or treatment-effect modeling and machine learning evaluation\nProficiency in Python, SQL & GCP\nStrong problem-solving, stakeholder management, and communication skills\nPreferred Qualifications\nExperience applying causal inference and experimentation in a business setting\nFamiliarity with cloud data platforms, modeling libraries, experimentation tools, and model deployment or 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