{"id":1246945,"url":"https://alion.io/job/isoftstone-senior-data-scientist","title":"Senior Data Scientist","company":{"id":1767282,"name":"iSoftStone","domain":"isoftstoneinc.com","url":"https://alion.io/company/isoftstoneinc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jobvite","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":150000,"currency":"USD","period":"year","gross":null,"usd_annual":150000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prophet","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-09-25T17:53:15Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-29T17:38:37Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Description\niSoftStone, Inc. is seeking a Senior Data Scientist to Join our Team!\n*This is aHybrid Role in the New York City Metro Area*\n**Client Site Travel Required- Up to 25%**\n***Candidates must have permanent authorization to work in the United States. Visa sponsorship is not available for this role.***\nThis role is a client-facing data scientist supporting enterprise retail accounts across merchandising, supply chain, customer, and pricing analytics. You'll work embedded with client teams - scoping the problem, building the model, and defending the methodology to business stakeholders who are not data people. This is a consulting role: billable, multi-account, and dependent on your ability to translate ambiguous business questions into tractable modeling problems.\nResponsibilities:\nOwn end-to-end delivery on retail analytics engagements: discovery, data assessment, feature design, modeling, validation, deployment handoff, and results readout.\nBuild and productionize models across the retail value chain - demand forecasting and inventory optimization, customer segmentation and CLV, price/promo elasticity and markdown optimization, assortment and allocation.\nDesign data models and semantic layers on client data platforms (Snowflake, Databricks, Fabric, BigQuery); work with data engineering to define the tables the models actually needrather than accepting what exists.\nInterrogate data quality and business logic before modeling - retail data is messy, and identifying the flaw in a returns table or a channel attribution rule is often worth more than a better algorithm.\nPresent findings to director- and VP-level client stakeholders; quantify business impact in margin, sell-through, GMROI, or working capital terms, not model metrics.\nSupport pre-sales: solution shaping, estimation, POC design, and technical credibility in client pitches.\nMentor junior analysts and contribute reusable accelerators to the retail practice.\nQualifications:\nFive+ years applied data science experience, with meaningful time on retail, CPG, or e-commerce problems.\nStrong data modeling fundamentals - dimensional modeling, star/snowflake schemas, slowly changing dimensions, grain definition. You should be able to look at a retail transaction feed and design the model, not just query it.\nAdvanced SQL and production-grade Python (pandas, scikit-learn, statsmodels); comfort with at least one of PyTorch/TensorFlow, Prophet/ARIMA-family forecasting, or causal inference frameworks.\nDemonstrated experience with time series forecasting and/or econometric modeling (elasticity, uplift, incrementality).\nCloud data platform experience (Snowflake, Databricks, Azure/AWS/GCP) and familiarity with CI/CD and version control practice.\nAbility to work directly with clients: run a working session, handle pushback on methodology, and write a deck that a merchant will actually read.\nBachelor's degree in a quantitativediscipline.\nPreferredQualifications:\nMathematics, Statistics, or Operations Research major - we specifically value candidates with formal mathematical training and the ability to reason from first principles about optimization, probability, and model assumptions.\nAdvanced degree (MS/PhD) in a quantitative field.\nRetail domain knowledge: open-to-buy, allocation, replenishment, size/pack optimization, omnichannel inventory, RFM and loyalty analytics.\nLLM/GenAI application experience in a retail context (demand sensing, agentic workflows, unstructured product or review data).\nConsulting or professional services background.\nExperience with retail systems data a plus- SAP, Salesforce Commerce Cloud, O9.\nPay rate:$130,000 to $150,000/year\niSoftStoneis a global IT service and consulting companythat creates value and drives success through technology solutions, service excellence, and digital innovation. We specialize in web and application development, software testing and support, data and content management, digital experience, accessibility, and data for machine learning and AI. With 20 delivery centers and more than 90,000 employees worldwide, iSoftStoneis proud to serve some of the world’s most well-known businesses, including 90+ Fortune Global 500 companies.\nVisit us at https://www.isoftstoneinc.com.\niSoftStoneis committed to the practice of equal opportunity for all its employees and applicants in employment, and does not discriminate on the basis of race or ethnicity, color, age, national origin, religion, creed, marital status, sex, pregnancy, gender, gender identity, sexual orientation, status as an honorably discharged veteran or disabled veteran or military status, political affiliation or belief, citizenship/status as a lawfully admitted immigrant authorized to work in the United States, or presence of any physical, sensory, or mental disability. In addition, reasonable accommodation will be made for known physical or mental limitations for all otherwise qualified personswith disabilities.","description_format":"text","description_chars":4953,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Information Technology","Professional Services","IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-09-25T17:53:15Z"}],"liveness":{"score":88,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.876,"p_room":1,"age_days":5,"expected_fill_days":23,"reasons":["conf:36","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":150000,"is_top_pay":false},"html_url":"https://alion.io/job/isoftstone-senior-data-scientist","json_url":"https://alion.io/job/isoftstone-senior-data-scientist.json","meta":{"generated_at":"2026-10-01T09:32:17Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":171,"day_limit":5000,"remaining_today":4829,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}