{"id":741701,"url":"https://alion.io/job/apprissretail-data-science-manager","title":"Data Science Manager (Full-Stack / Production ML)","company":{"id":669638,"name":"Appriss Retail","domain":"apprissretail.com","url":"https://alion.io/company/apprissretail","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":null},"role":"Frontend","role_family":"Frontend","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":123000,"max_usd":234000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":55},"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"MLFlow","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Tool Use","optional":false},{"name":"dbt","optional":true},{"name":"Fine-tuning","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"RAG","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-10T13:36:23Z","employer_posted_date":"2026-06-10","last_verified_at":"2026-10-11T17:44:31Z","board_verified":true,"closed_at":null,"days_open":123,"trust":{"level":"stale","repost_count":1,"flags":["stale"],"days_open":122},"description":"About Appriss Retail\nAppriss Retail is the total retail loss solution for omnichannel, unifying high-quality data across stores, online, and customer ser-vice to reduce returns, cut shrink, and manage incidents. Our products-Engage to reduce returns, Secure to cut shrink, and Incident to centralize visibility-help retailers move from reactive loss control to strategic profit protection. Together, they empower organizations to make better operations decisions, strengthen accountability, and puthundreds of millions back to the bottom line. Covering 40% of all U.S. transactions and active in 45 countries, Appriss Retail is trusted by 60+ of the top 100 U.S. retailers to deliver lasting performance improvement. Learn more at apprissretail.com.\nOverview\nWe are looking for a player-coach who leads a small, high-output data science team while staying deeply hands-on. This role owns the full scope of data science at Appriss Retail - data engineering, governance, and production model delivery - not just model building. The right candidate has built and shipped realdataplatforms andAI/ML systems using a modern stack, has meaningful experience with LLMs and agentic architectures, and canoperatecredibly in both the technical weeds and the business conversation.\nAs a Data Science Manager with 2-4 direct reports from day one, you would set technical direction for the team. This is not a role for someone who manages from a distance. You will write code, review pipelines, define data contracts, and drive architectural decisions - while also growing and directing the team around you.\nThis is a full-stack role, not a model-building role with a handoff. If your last few projects ended when you handed a notebook or a trained model to a data engineering or ML engineering team to put into production, this probably isn’t the right fit.\nEssential Duties\nTechnical leadership & delivery\nOwn end-to-end delivery of high-impact data science projects - from ambiguous businessrequestto production-readysystem.\nDesign andmaintaindata pipelines, data models, and governance standards alongside your team; treat infrastructure as a first-class product concern.\nBuild, evaluate, and iterate on ML models in production; lead experimentation rigor, monitoring, and lifecycle management.\nArchitect and ship LLM-integrated features and agentic workflows - including prompt engineering,tool use, and output evaluation.\nGuidecloud infrastructurearchitecturefordata scienceprojects, taking into accountperformance,maintenance, and cost criteria.\nSet the standard for code quality: write production-grade Python and SQL, enforce reviewpractices, andmaintaindocumentation.\nPartner closely with engineering to integrate models and pipelines into core product infrastructure.\nPeople & team\nDirectly manage 2-4 data scientists; provide technical mentorship, career development, and clear performance expectations.\nDefine team operating norms: sprint planning, code review, documentation, and delivery accountability.\nRecruit and grow the team as the function scales.\nStrategy & stakeholders\nTranslate ambiguous business problems into well-scoped analytical and modeling work with defined success criteria.\nPartner with product, engineering, and business stakeholders to ensure data work is grounded in real source systems and product context - not isolated analysis.\nContribute to the data and analytics roadmap, balancing near-term delivery with longer-term platform investment.\nCommunicate clearly to non-technical audiences; influence decisions with data and model outputs.\nRequired Qualifications\nExperience\n6+ years of experience in data science, data engineering, or a closely related technical discipline.\n1+yearof direct people management or formal technical lead experience over a team.\nTechnical skills - required\nExpert-level SQL and Python; production code, not just analysis scripts.\nDeep understanding of data infrastructure: pipelines, warehousing, data modeling, and source system behavior.\nStrong software engineering practices: version control, code review, testing, and has built or maintained a CI/CD pipeline for a data or ML workload..\nAbility to scope and deliver complex analytical projects independently from vague inputs.\nCloud data platform experience: Snowflake, Azure (preferred), AWS, or GCP.\nWorking knowledge of infrastructure-as-code (Terraform, CloudFormation, or equivalent) and containerization (Docker, and ideally Kubernetes or a managed container service).\nHas made and defended a build-vs-buy or cost/latency tradeoff on a production ML or data system.\nFamiliarity with ML platform tooling: MLflow, feature stores, model registries, or similar.\nRequired Education\nMaster's degree or Bachelor's Degree in a technical, quantitative field\nPreferred Qualifications\nProficiencywith modern data stack tooling:dbt, Airflow, Spark, or equivalent.\nDemonstrated LLM experience: prompt engineering, RAG, fine-tuning, or agent frameworks(LangChain,LlamaIndex, or equivalent)\nExperience and familiarity with agentic AI architectures: multi-step reasoning, tool use, memory, and orchestration.\nExperience in retail, fraud detection, or transaction-level data at scale.\nInterview Process / What to Expect\nIn addition to a technical deep-dive on your modeling skills, the interview process includes a system design conversation where you’ll walk through how you’d architect, deploy, and operate a model or pipeline in production - including infra and cost tradeoffs.\nBenefits\nAt Appriss Retail, we offer a competitive and comprehensive benefits package designed to support your well-being at work and beyond. Benefits begin on your first day and include multiple medical plan options, dental and vision coverage, health savings and flexible spending accounts, paid parental leave, and supplemental coverage for life’s unexpected moments. We offer generous paid time off, a 401(k) with immediate vesting and company match, short- and long-term disability, and free access to health and wellbeing resources such as Calm and Sworkit. You’ll also have access to learning and development opportunities to help you grow your career. Our benefits support your well-being so you can perform your best in every part of life.\nReports to:Director of Data Science\nDepartment:Data Science\nSupervisory Duties: Yes, direct management of 2-4 data scientists.\nTravel Required: Yes, up to 10% for training and conferences\nLocation/Work Region: Remote - United States\nThis job is eligible for a 12-15% bonus in addition to the base salary.\nWe are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to protected characteristics.","description_format":"text","description_chars":6694,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Parental leave"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Professional Services","Sales & Marketing"],"lifecycle":[{"event":"open","at":"2026-09-11T12:51:44Z"},{"event":"close","at":"2026-09-17T13:35:38Z"},{"event":"reopen","at":"2026-10-08T19:23:15Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long shot","p_open":1,"p_active":0.377,"p_room":0.28,"age_days":121,"expected_fill_days":33,"reasons":["conf:2","win:tail","crowd:"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/apprissretail-data-science-manager","json_url":"https://alion.io/job/apprissretail-data-science-manager.json","meta":{"generated_at":"2026-10-11T19:36:05Z","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":6638,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-12T00:00:00Z"}},"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":669638},"rest":"https://alion.io/mcp/rest/get_company?id=669638"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fapprissretail-data-science-manager"},{"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%2Fapprissretail-data-science-manager"},{"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%2Fapprissretail-data-science-manager"},{"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/apprissretail-data-science-manager\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fapprissretail-data-science-manager"}]}