{"id":3587925,"url":"https://alion.io/job/citi-lead-data-scientist-vp","title":"Lead Data Scientist / VP","company":{"id":7841,"name":"Citi","domain":"citi.com","url":"https://alion.io/company/citi","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":98,"open_postings":557,"ghost_share":0.009,"stale_share":0.206,"repost_share":0.068,"time_to_fill_p50_days":9,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Data Science","role_family":"Data Science","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mississauga, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":111600,"max":161600,"currency":"CAD","period":"year","gross":null,"usd_annual":115672},"salary_estimate":null,"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":"CrewAI","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Hallucination","optional":false},{"name":"JavaScript","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"Semantic Search","optional":false},{"name":"SHAP","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-30T00:00:00Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-08T15:26:13Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"The Lead Data Scientist will work hands-on across the AI and analytics development lifecycle. The role will design analytical approaches, develop and validate models, build Generative AI and agentic workflows, and partner with data engineers and technology teams to implement scalable production solutions.\nThe successful candidate will combine strong data-science expertise with practical engineering skills, enterprise implementation experience, and an understanding of governance requirements. The role will also provide technical guidance to other data scientists and help establish reusable methods, coding standards, and implementation practices.\nKey Responsibilities\nAdvanced Analytics and Statistical Modeling\nDesign and implement statistical analyses, predictive models, machine-learning solutions, and analytical frameworks.\nTranslate workforce and organizational questions into measurable hypotheses, appropriate methodologies, and actionable insights.\nApply techniques such as regression, classification, clustering, survival analysis, forecasting, experimentation, and causal inference.\nPerform feature engineering, variable selection, model tuning, validation, sensitivity testing, and performance evaluation.\nApply explainability methods such as SHAP, feature attribution, and scenario analysis.\nClearly document and communicate analytical assumptions, limitations, findings, and business implications.\nGenerative AI and Agentic Solutions\nDesign and build Generative AI applications, Retrieval-Augmented Generation solutions, and agentic workflows.\nImplement tool calling, workflow orchestration, structured outputs, multi-turn interactions, and state management.\nIntegrate foundation models through approved enterprise gateways and cloud platforms.\nDevelop reusable prompts, agents, tools, evaluation components, and analytical services.\nBuild evaluation frameworks to measure accuracy, groundedness, retrieval quality, task completion, consistency, and hallucination risk.\nTest and optimize solutions for reliability, performance, latency, cost, and user experience.\nData Engineering and Solution Implementation\nPartner with data engineers and architects to design data pipelines, analytical datasets, feature-generation processes, APIs, and production integrations.\nDevelop clean, reusable, and well-documented Python and SQL code for analytical and AI solutions.\nWork with structured and unstructured data from multiple enterprise sources.\nImplement data-quality checks, logging, monitoring, error handling, and traceability within analytical workflows.\nSupport the development of feature libraries, embedding pipelines, vector-search capabilities, and model services.\nMove prototypes into scalable production solutions using established MLOps and LLMOps practices.\nGovernance and Responsible AI\nEnsure solutions comply with applicable Model Risk Management, privacy, cybersecurity, data-governance, and responsible AI requirements.\nImplement appropriate access controls, data entitlements, PII protections, cohort-suppression rules, and analytical safeguards.\nConduct model-performance, explainability, bias, fairness, stability, and outcome testing.\nSupport controls for prompt-injection detection, approved tool use, source grounding, and model-output validation.\nPrepare documentation covering methodologies, data dependencies, testing, limitations, controls, and implementation decisions.\nPartner with risk and control functions to address findings and support required reviews.\nTechnical Leadership and Collaboration\nServe as a technical lead for complex data-science and AI initiatives while remaining a hands-on individual contributor.\nProvide technical guidance and peer review to data scientists working on related solutions.\nHelp establish standards for coding, analytical design, model validation, testing, documentation, and deployment.\nPartner with product managers, data engineers, architects, technology teams, and business stakeholders throughout implementation.\nPresent complex technical concepts and analytical results in clear language for business and senior stakeholders.\nContribute to delivery planning, solution design, technical decision-making, and resolution of implementation issues.\nQualifications and Required Skills\nExperience\nTypically, six or more years of relevant experience in data science, machine learning, statistical modeling, advanced analytics, AI implementation, or a related field.\nDemonstrated experience implementing analytical, machine-learning, or AI solutions in an enterprise environment.\nExperience moving solutions from research and prototyping through validation, production deployment, and monitoring.\nAbility to lead complex technical work independently and collaborate effectively across multidisciplinary teams.\nExperience operating within a regulated environment is beneficial.\nTechnical Expertise\nStrong knowledge of statistical modeling, probability, regression, classification, clustering, forecasting, experimentation, and model validation.\nAdvanced proficiency in Python and libraries such as Pandas, NumPy, SciPy, Scikit-learn, Statsmodels, PyTorch, or TensorFlow.\nStrong SQL skills and experience with data extraction, transformation, analytical cohort development, and data-quality testing.\nExperience designing or implementing Generative AI, Retrieval-Augmented Generation, tool-calling, or agentic applications.\nFamiliarity with frameworks such as Google Agent Development Kit, LangGraph, LangChain, CrewAI, or comparable technologies.\nExperience integrating foundation models through enterprise AI platforms such as Google Cloud and Vertex AI, Microsoft Azure, or AWS.\nUnderstanding of APIs, data pipelines, vector embeddings, semantic search, and production integration patterns.\nFamiliarity with MLOps or LLMOps practices, including versioning, testing, deployment, observability, monitoring, and change management.\nKnowledge of responsible AI, model explainability, bias and fairness testing, data privacy, and role-based access controls.\nBeneficial Experience\nExperience in People Analytics, Workforce Planning, Human Capital Management, organizational effectiveness, or financial-services analytics.\nExperience working with sensitive workforce data and governed analytical environments.\nFamiliarity with enterprise software-development practices, source control, automated testing, and CI/CD.\nStrong written and verbal communication skills, including the ability to explain technical methods to non-technical audiences.\nEducation\nMaster’s degree or Ph.D. in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or another quantitative discipline.\nA bachelor’s degree with substantial relevant technical and implementation experience may also be considered.\nMaster's degree in Analytics, Data Science, Computer Science.\n6+ Years of experience in Engineering or HR Technology.\nExperience with Python and JavaScript\nAI Automation.\n------------------------------------------------------\nJob Family Group:\nDecision Management------------------------------------------------------\nJob Family:\nSpecialized Analytics (Data Science/Computational Statistics)------------------------------------------------------\nTime Type:\nFull time------------------------------------------------------\nPrimary Location Full Time Salary Range:\n$111,600.00 - $161,600.00------------------------------------------------------\nMost Relevant Skills\nPlease see the requirements listed above.------------------------------------------------------\nOther Relevant Skills\nFor complementary skills, please see above and/or contact the recruiter.------------------------------------------------------\nAutomated Processing and AI\nWe use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.\nImportantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.\n------------------------------------------------------\nThis job opening is for an existing job vacancy.\n------------------------------------------------------\nCiti is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.\nIf you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.\nView Citi’s EEO Policy Statement and the Know Your Rights poster.","description_format":"text","description_chars":9157,"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":[],"hiring_locations":[{"name":"Canada","iso":"CA","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Cards & Card Issuing","Wealth Management & Financial Advisors","Payment Processing & Gateways","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-11-01T14:44:38Z"}],"visa":[],"liveness":{"score":49,"band":"ok","label":"Likely open","p_open":1,"p_active":0.889,"p_room":0.55,"age_days":9,"expected_fill_days":9,"reasons":["conf:1","velocity","win:tail","comp:brand"],"computed_at":"2026-11-08T05:47:12Z"},"pay":{"stated_usd_annual":115672,"is_top_pay":false},"html_url":"https://alion.io/job/citi-lead-data-scientist-vp","json_url":"https://alion.io/job/citi-lead-data-scientist-vp.json","meta":{"generated_at":"2026-11-09T02:01:15Z","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":4277,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-10T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"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":7841},"rest":"https://alion.io/mcp/rest/get_company?id=7841"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fciti-lead-data-scientist-vp"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"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%2Fciti-lead-data-scientist-vp"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"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%2Fciti-lead-data-scientist-vp"},{"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/citi-lead-data-scientist-vp\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fciti-lead-data-scientist-vp"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3587925}},{"tool":"search_jobs","arguments":{"company":"citi.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3587925},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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