{"id":2519403,"url":"https://alion.io/job/valerie-group-global-data-analytics-expert","title":"Global Data Analytics Expert","company":{"id":685122,"name":"Valerie Group","domain":"valeriegroup.com","url":"https://alion.io/company/valeriegroup","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18000,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"BigQuery","optional":true},{"name":"dbt","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Machine Learning","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-10-14T07:41:01Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T15:59:51Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About the Role\nWe are looking for a rigorous, systems-minded quantitative leader to own our core commercial intelligence engine end-to-end. This is not a traditional dashboard-building or BI reporting seat. You will define, build, and encode the mathematical logic, unit-economic models, and predictive forecasting systems that power our product and drive real commercial decisions for our brands.\nYou will sit at the intersection of finance, data science, and product engineering, turning complex commercial data, messy founder inputs, and predictive models into defensible, automated product logic and AI agent workflows.\nKey Accountabilities\n1. Proprietary Systems: Growth Forecasts & P&Ls\nGrowth Forecasting: Build and own the methodology that takes a brand’s current performance and projects a defensible 12-month forecast, complete with a rigorous assumption set.\n\nFinancial Architecture: Construct brand-level P&Ls directly from the forecast, mapping revenue, COGS, contribution margin, and operating costs.\n\nVariance & Calibration: Continuously run models against real outcomes, measure errors, track actuals against projections, and explain every variance.\n\n2. Productization & Agentic Workflow Design\nProduct Logic: Translate sophisticated financial and statistical models into production-ready product logic so the system calculates and delivers outputs natively.\n\nAI Agent Specification: Define what data agents compute, what internal data/benchmarks they draw on, and what assertions they are strictly barred from making.\n\nHuman-in-the-Loop Orchestration: Replace manual validation with automated product rules while establishing clear review gates for human sign-off before deliverables ship.\n\nData Schemas & Engineering Collaboration: Specify data structures, validation rules, and pipelines across structured commercial inputs, partnering directly with engineering to bring models to life in production.\n\n3. Decision Framing & Commercial Rigor\nDecision-First Modeling: Design every analysis backwards from the specific commercial decision it is meant to change.\n\nUncertainty & Stated Confidence: Size uncertainty statistically, state clearly what sparse or self-reported data cannot support, and attach a stated confidence level to every output.\n\nBenchmark Library Management: Define and version the benchmark repository (category, stage, market) to evaluate brands accurately even when data is sparse.\n\n4. Enablement & Commercial Communication\nCross-Functional Communication: Present complex numbers, models, and uncertainties to founders and operators with clarity and authority.\n\nQuantitative Literacy: Raise the analytical bar across the business by teaching teams how to read and interpret model outputs correctly.\n\nDocumentation & Standards: Write airtight documentation and standards for data/finance deliverables so cross-functional delivery teams can execute autonomously.\n\nWhat This Seat Is Not\nNot a BI/Reporting Seat: Dashboards are merely one downstream output of this work; your primary focus is proprietary modeling and product architecture.\n\nNot Research Without Action: We judge models by the decisions they actually changed, not academic complexity.\n\nNot a Data Engineering Seat: You will specify pipelines, schemas, and logic for engineering to build-you won't be maintaining core infrastructure tables yourself.\n\nIdeal Background & Qualifications\nMust-Haves\nExperience: 6-8 years in growth, marketing, commercial, or product analytics within DTC, e-commerce, marketplaces, or specialized platforms.\n\nProven Track Record: End-to-end ownership of a forecasting, unit-economics, or media-mix model that commercial teams relied on for high-stakes budget or strategic decisions. You can name the decisions your model changed and what followed.\n\nDTC Unit Economics Mastery: Deep fluency in CAC, AOV, COGS, contribution margin, LTV, payback period, breakeven, retention cohorts, and working capital reconciliation.\n\nModelling with Incomplete Data: Demonstrated ability to build robust outputs from banded, self-reported, or partial founder inputs while explicitly quantifying confidence levels.\n\nStatistical Rigor: Strong foundation in sizing uncertainty, managing sample limitations, and maintaining analytical integrity.\n\nTechnical Depth: Hands-on daily fluency in SQL and Python.\n\nProduct & Engineering Collaboration: Experience working directly with engineering teams to turn quantitative models or metric definitions into production software.\n\nCommunication: Exceptional presence and ability to defend underlying assumptions and model uncertainty under direct challenge.\n\nNice-to-Haves\nMedia mix modeling (MMM), incrementality testing, or causal measurement methodologies.\n\nApplied machine learning experience (forecasting, propensity, or segmentation models in production).\n\nExperience evaluating generative AI or multi-agent system outputs.\n\nFamiliarity with modern data stack layers (Snowflake, BigQuery, dbt) and attribution platforms (Triple Whale, Northbeam, Rockerbox).\n\nExposure to multi-brand ecosystems via agency, consulting, or platform environments.\n\nExperience in early-stage product environments where models and products were co-developed from scratch.\n\nThe best time to join Valerie was yesterday. The next best time is now \nOur Hiring Process\nWe want interviews to be valuable for both sides. Throughout the process, you'll meet the people you'll work with, learn more about the role, and get a chance to understand how we think and operate.\nOur process typically includes:\nIntroductory conversation with our Talent team 30 mins\n\nHiring Manager interview 30-45 mins\n\nRole-specific assessment or practical exercise (where applicable)\n\nCross-functional or stakeholder interviews 30-45 mins\n\nFinal conversation with leadership 30-45 mins\n\nWe'll always let you know what to expect before each stage.\nWhat You Can Expect\nMeaningful work with visible impact\n\nHigh ownership from day one\n\nCollaboration with experienced founders, operators, and specialists\n\nA team that values curiosity, initiative, and continuous improvement\n\nCompetitive compensation and the tools you need to do your best work\n\nOpportunities to grow as Valerie grows\n\nValerie is committed to building an inclusive workplace where people from different backgrounds, experiences, and perspectives can thrive. We hire based on skills, potential, and the ability to contribute to our team.","description_format":"text","description_chars":6400,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["E-commerce Marketing","Digital Marketing"],"lifecycle":[{"event":"open","at":"2026-10-14T10:34:43Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":31,"reasons":["conf:1","win:early"],"computed_at":"2026-10-15T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/valerie-group-global-data-analytics-expert","json_url":"https://alion.io/job/valerie-group-global-data-analytics-expert.json","meta":{"generated_at":"2026-10-15T16:27:54Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":25087,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-16T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":685122},"rest":"https://alion.io/mcp/rest/get_company?id=685122"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fvalerie-group-global-data-analytics-expert"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fvalerie-group-global-data-analytics-expert"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fvalerie-group-global-data-analytics-expert"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/valerie-group-global-data-analytics-expert\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fvalerie-group-global-data-analytics-expert"}]}