{"id":1650419,"url":"https://alion.io/job/sciemo-data-scientist","title":"Data Scientist","company":{"id":3854753,"name":"Sciemo","domain":"sciemo.ai","url":"https://alion.io/company/sciemo","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","Raleigh, United States","Atlanta, United States","Philadelphia, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"AWS","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-24T15:22:23Z","employer_posted_date":"2026-08-24","last_verified_at":"2026-10-09T22:32:43Z","board_verified":true,"closed_at":null,"days_open":46,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":46},"description":"about sciemo\nSciemo builds AI for consumer goods: technology that helps businesses make faster, smarter, and more human decisions across the entire IBP process. From optimizing promotions to balancing demand and supply, Sciemo's platform transforms messy, siloed data into measurable business impact. Its AI agents assist decision-makers in real-time, turning complexity into clarity. We are headquartered in New York City.\nROLE\nAs a Data Scientist, you will build the models that turn customer data into decisions - forecasting, optimization, measurement, and the analysis that tells us whether any of it is working.\nYou'll work across the full lifecycle: understanding a business problem, exploring the data, developing and validating models, and partnering with engineers to get them into production. You'll also work directly with customer data and customer-facing teams, which means your analysis needs to hold up under scrutiny from people whose decisions depend on it.\nThis role is a strong fit for someone earlier in their career who wants real ownership quickly. You'll get direct mentorship from our Co-Founder & CAIO and senior engineers, and the scope to grow fast.\nRESPONSIBILITIES\nModeling & Analysis\nDevelop, validate, and iterate on models for forecasting, optimization, anomaly detection, and measurement.\nPerform exploratory analysis on complex customer datasets to surface patterns worth acting on.\nDesign and analyze experiments; build the measurement approaches that quantify business impact.\nEstablish rigorous validation practices - backtesting, holdouts, and honest error analysis.\nProduction & Collaboration\nPartner with ML and data engineers to move models from notebook to production.\nContribute to feature engineering, evaluation pipelines, and model monitoring.\nWrite clean, reproducible Python that other people can read and build on.\nBusiness Impact\nTranslate business questions into analytical problems, and analytical results back into recommendations.\nCommunicate findings clearly to internal teams and customers, including non-technical audiences.\nFollow deployed models into the real world and help make sure they're delivering what we promised.\nALL ABOUT YOU\nExperience developing and validating models on real, messy data - through internships, prior roles, or substantive project work.\nSolid foundation in statistics and machine learning: regression, time series, tree-based methods, experimental design.\nStrong Python (pandas, scikit-learn, and the surrounding ecosystem) and strong SQL.\nCuriosity about the business problem behind the data, not just the modeling technique.\nClear communication - you can explain what you did, why, and what it means, to someone who doesn't do this for a living.\nStrong problem-solving skills, adaptability, and a \"hacker\" mentality.\nEagerness to learn quickly in a startup environment.\nNice to have\nExposure to CPG, retail, or consumer brand data.\nExperience with Spark, cloud platforms (AWS or similar), or orchestration tools.\nFamiliarity with LLMs and their practical use in analytical workflows.\nBENEFITS & PERKS\nCheck out our one pager!\nLOCATION\nHybrid role based in New York City; open to remote U.S. candidates willing to travel monthly to our NYC office.\nequal opportunity employer\nWe are an equal opportunity employer and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. 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