{"id":1998803,"url":"https://alion.io/job/standard-chartered-data-ai-ops-lead","title":"Data & AI Ops Lead","company":{"id":20709,"name":"Standard Chartered","domain":"sc.com","url":"https://alion.io/company/standard-chartered-gbs","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":25000,"max_usd":61000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":31},"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":"Context Engineering","optional":false}],"status":"live","first_seen_at":"2026-10-07T10:14:18Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T20:31:18Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Job Summary\nThe Data & AI Lead is responsible for identifying, shaping, and delivering AI-enabled products that improve risk and compliance processes and deliver measurable business value.\nThe role sits within the AI Centre of Excellence (CoE) and acts as the bridge between business, data, AI engineering, and governance teams, ensuring AI solutions are aligned to strategic priorities, deliver tangible outcomes, and are successfully adopted by business users.\nIn addition to product ownership, the role drives process excellence and value realisation, ensuring AI initiatives generate measurable productivity, risk reduction, and operational efficiency improvements.\nKey Responsibilities\nStrategy\nDefine and maintain the Data & AI capability strategy and product roadmap for Risk & Compliance, ensuring AI initiatives are aligned to business priorities, enterprise AI direction and measurable value outcomes.\nOwn the AI use case portfolio across assisted, enabled, generative and agentic automation, ensuring a coherent path from ideation to prioritisation, design, delivery, adoption, scale and retirement.\nPartner closely with respective Product Owners, Business Owners and Process Owners to review the full product and process journey, identifying where AI, data, automation and analytics can materially improve productivity, risk outcomes, user experience and decision quality.\nLead structured opportunity discovery across products and processes to identify areas where process engineering through AI and data tools can deliver substantial qualitative and quantitative benefits, including cycle-time reduction, effort elimination, quality improvement, control uplift and improved decision support.\nContinuously challenge existing ways of working and push the boundaries of imagination with business stakeholders by bringing practical ideas on GenAI, agentic AI, workflow automation, data intelligence and reusable AI capability patterns.\nSupport strategic buy, build, reuse or partner decisions for AI capabilities, ensuring investment is directed towards scalable, reusable and value-accretive solutions.\nMaintain a centralised AI backlog and product pipeline that balances business value, feasibility, risk, complexity, user adoption, delivery capacity and strategic relevance.\nBusiness\nAct as the primary business-facing lead for AI capability development, building trusted relationships with Product Owners, Business Owners, SMEs and senior stakeholders to identify, shape and deliver AI-enabled business transformation.\nWork with product and business owners to assess the entire product journey, including upstream inputs, workflow steps, decision points, controls, handoffs, pain points, downstream outputs and user experience.\nTranslate business challenges into clear, outcome-led AI opportunities, ensuring each use case has a defined problem statement, target user group, expected benefit, success measure and adoption pathway.\nLead process and value analysis to determine where AI and data tools can generate measurable business impact, including productivity gains, cost avoidance, improved quality, better risk detection, reduced manual intervention and enhanced decision-making.\nQuantify expected benefits before implementation and track realised benefits after deployment, covering both quantitative measures such as time saved, volume processed, cost avoided and cycle-time reduction, and qualitative outcomes such as improved user confidence, better insights, stronger controls and improved service experience.\nEnable product and business owners to reimagine how work can be performed using AI, including GenAI assistants, copilots, agentic workflows, intelligent triage, automated summarisation, insight generation and decision-support tools.\nEnsure AI products are business-relevant, user-centred, measurable, scalable and designed to deliver sustained adoption rather than isolated experimentation.\nProcesses\nEstablish and operate a structured AI product lifecycle covering intake, opportunity discovery, journey review, prioritisation, requirements definition, design, development oversight, deployment readiness, adoption, value tracking and continuous improvement.\nFacilitate end-to-end product journey and process engineering reviews with Product Owners and Business Owners to identify friction, duplication, manual effort, control gaps, rework, delays and decision bottlenecks that can be improved through AI and data-enabled solutions.\nConvert business and process opportunities into well-defined product artefacts, including product requirement documents, user journeys, process maps, feature definitions, prioritisation criteria, value hypotheses and delivery roadmaps.\nWork closely with AI engineering, data and analytics teams, GenAI prompt specialists, governance teams and business SMEs to ensure AI solutions are designed and delivered against clearly defined business outcomes.\nOversee use case delivery from ideation through deployment, ensuring delivery progress, dependencies, risks, milestones, design decisions, readiness activities and business adoption plans are actively managed.\nDefine and maintain value measurement approaches, including baseline metrics, benefit assumptions, productivity scorecards, adoption dashboards, value realisation tracking and portfolio performance reporting.\nUse feedback from users, adoption metrics, operational outcomes, process performance and governance inputs to continuously improve AI products, backlog priorities and product journey design.\nPeople & Talent\nBuild and own strong working relationships with Product Owners, Business Owners, Process Owners, Technology, Data, Risk, Compliance and AI Governance teams to create a shared agenda for AI-enabled transformation.\nAct as a trusted advisor to business teams by helping them understand what is possible with AI, GenAI, agentic AI, data products and automation, while translating ambition into practical, deliverable and governed use cases.\nFacilitate ideation sessions, product clinics, journey walkthroughs and design workshops that encourage stakeholders to rethink how processes, controls and decisions could be redesigned using AI and data.\nBuild confidence and adoption across business teams by partnering with learning, engagement and change teams to deliver training, demos, playbooks, engagement plans and user enablement activities.\nPromote a product and value-led mindset across AI delivery teams, ensuring teams remain focused on user outcomes, measurable impact, adoption, continuous improvement and responsible innovation.\nEncourage a culture of curiosity, experimentation and disciplined execution, where teams are empowered to challenge legacy processes and explore ambitious but controlled uses of AI.\nSupport the development of AI fluency across business stakeholders by sharing reusable examples, emerging use cases, lessons learned and practical patterns for applying AI to real business problems.\nRisk Management\nEnsure AI use cases are shaped and delivered in line with enterprise AI governance, responsible AI, data, risk, compliance, security and regulatory expectations.\nWork with Product Owners and Business Owners to identify risks across the full product journey, including process risks, control gaps, data risks, adoption risks, operational risks, model risks and inappropriate automation risks.\nPartner with AI Governance, Risk, Compliance and assurance teams to ensure appropriate validation, explainability, bias assessment, control requirements, monitoring inputs and approval evidence are built into product delivery.\nEnsure AI-enabled process engineering does not compromise control effectiveness, accountability, data integrity, customer outcomes, regulatory expectations or operational resilience.\nIdentify and manage delivery risks, dependency risks, value realisation risks, user adoption risks and operational readiness risks across the AI portfolio, escalating material issues where required.\nEnsure AI products are implemented with appropriate human oversight, usage boundaries, business readiness, control documentation, monitoring inputs and feedback mechanisms to support sustainable and controlled use.\nUse qualitative and quantitative performance insights to identify where deployed AI products may require refinement, additional controls, retraining, user education, redesign or retirement.\nGovernance\nMaintain transparent governance over the AI product portfolio, including roadmap status, prioritisation decisions, product journey reviews, delivery progress, adoption performance, value realisation and key risks.\nEnsure each AI use case has clear ownership across Product Owner, Business Owner, delivery team and governance stakeholders, with defined accountability for business outcomes, adoption, controls and value tracking.\nProvide regular reporting to senior stakeholders and governance forums through AI portfolio dashboards, value dashboards, ROI tracking reports, adoption metrics and portfolio performance updates.\nSupport governance forums with evidence-based recommendations on prioritisation, investment, scaling, remediation, redesign or retirement of AI products.\nMaintain disciplined portfolio controls so AI initiatives are traceable, measurable, outcome-led and aligned to business priorities, responsible AI expectations and enterprise governance standards.\nEnsure product journey reviews, benefit cases, design decisions, user impacts, adoption evidence and value realisation outcomes are appropriately documented and available for management review.\nCreate a continuous improvement governance loop where feedback from Product Owners, Business Owners, users, delivery teams and governance stakeholders is used to refresh the roadmap, backlog, adoption approach and value strategy.\nKey Deliverables\nAI product roadmap & portfolio backlog (including generative & agentic AI initiatives) aligned to Risk & Compliance strategic priorities.\nEnd-to-end process re-engineering blueprint co-created with product/business owners (leveraging generative & agentic AI) to transform key Risk & Compliance processes.\nCentral AI use case intake & prioritization framework ensuring value-driven selection and disciplined stage-gate development of AI solutions.\nAI adoption strategy & integration plan (with clear adoption KPIs) to drive and measure widespread usage of new AI and data tools across Risk & Compliance teams.\nBusiness enablement playbook & training modules to build R&C team proficiency and trust in advanced AI tools (e.g., generative & agentic AI solutions).\nAI value measurement framework & dashboards tracking qualitative and quantitative benefits (productivity, risk reduction, ROI) delivered by deployed AI initiatives.\nAI governance compliance documentation and requisite risk & compliance approvals for each AI product, evidencing Responsible AI and regulatory adherence.\nExecutive portfolio performance reports for R&C leadership highlighting AI-driven value creation, adoption progress, and future advanced AI opportunities.\nRegulatory & Business Conduct\nDisplay exemplary conduct and live by the Group’s Values and Code of Conduct.\nTake personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.\nEffectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.\nKey Stake Holders\nAI Engineering Solution development\nData & Analytics Data products and datasets\nGenAI Specialists Prompt design and context engineering\nAI Assurance Model validation and governance\nAI Operations Monitoring and lifecycle management\nBusiness Units AI adoption and value realisation\nSkills and Experience\nExperience in product management, data analytics, or digital transformation\nStrong knowledge of risk, complian...","description_format":"text","description_chars":14681,"description_truncated":true,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Annual leave","Continuous learning","Flexible schedule","Life insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services","Commercial & Retail Banks","Wealth Management & Financial Advisors","Investment Banking & M&A Advisory"],"lifecycle":[{"event":"open","at":"2026-10-07T10:14:18Z"}],"visa":[],"liveness":{"score":38,"band":"fade","label":"Fading","p_open":1,"p_active":0.693,"p_room":0.55,"age_days":4,"expected_fill_days":4,"reasons":["conf:11","velocity","win:tail","comp:brand"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/standard-chartered-data-ai-ops-lead","json_url":"https://alion.io/job/standard-chartered-data-ai-ops-lead.json","meta":{"generated_at":"2026-10-12T23:55:05Z","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":39304,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"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":20709},"rest":"https://alion.io/mcp/rest/get_company?id=20709"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fstandard-chartered-data-ai-ops-lead"},{"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%2Fstandard-chartered-data-ai-ops-lead"},{"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%2Fstandard-chartered-data-ai-ops-lead"},{"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/standard-chartered-data-ai-ops-lead\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fstandard-chartered-data-ai-ops-lead"}]}