Top Tech Jobs & Startup Jobs

Leads personal loan acquisition data science, developing and deploying machine learning models for customer targeting, campaign optimization, underwriting, pricing, and verification. Partners with data scientists, engineers, and product managers; analyzes large-scale numeric and textual data using Python, Spark, AWS, and related technologies; validates and backtests models; translates technical findings into business outcomes; and develops team talent.

Leads treasury strategy, liquidity and cash management, forecasting, funding, controls, risk mitigation, process improvement, executive reporting, and a team of finance professionals. Partners cross-functionally with Finance, Product, Risk, business leaders, external partners, and financial institutions. Oversees financial performance reporting, variance analysis, operating plans, investment analysis, expense management, and FP&A processes while developing scalable, automated financial solutions.

Own and prioritize product roadmaps for Capital One’s card acquisitions decisioning platform. Lead cross-functional delivery teams, translate business epics into features and user stories, define acceptance criteria, use data-driven hypotheses, manage risk, and collaborate with technology, design, data science, and business stakeholders to deliver customer-focused digital products.

Leads HR Operations and Risk strategy, shared services, governance, delivery models, and enterprise HR initiatives in India and globally. Partners with HR leaders to improve decision-making, employee experience, accountability, and operational efficiency. Drives change management, data-informed prioritization, stakeholder collaboration, talent development, and continuous improvement while managing evolving business needs and risks.

Manage enterprise risk practices by partnering with risk advisors, business teams, data management, and risk offices. Support audits and examinations, execute special projects, assess processes and controls, provide actionable recommendations, and improve risk management practices through analytical problem-solving. The role requires experience in risk management, audit, or quality assurance, along with data querying, scripting, and process and project management expertise.

Leads financial and strategic analysis for Capital One’s Card business, including industry benchmarking, macroeconomic trend analysis, portfolio health deep-dives, and executive reporting. Partners with Card Finance, Strategy, Business Lines, CRM, technology, credit, and operations teams to identify opportunities, solve business problems, and recommend actions supporting growth and profitability. Presents insights to senior leaders and develops fellow analysts.

Designs, develops, deploys, and supports production AI systems, including foundation models, LLM inference, agentic workflows, guardrails, evaluation, and observability. Owns complex AI architecture, reliability objectives, governance, and optimization for cost, latency, throughput, and hardware utilization. Partners across engineering, research, product, and program teams; leads technical reviews; contributes to long-term platform strategy; and mentors senior technical associates.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, agentic workflows, vector search, guardrails, evaluation, and multi-model orchestration. Optimizes AI systems for cost, latency, throughput, scalability, and hardware utilization. Leads governance reviews and design councils, contributes to technical roadmaps, establishes responsible AI standards, and mentors senior engineering leaders.

Leads large-scale machine learning initiatives, delivering production ML models, software, data pipelines, and cloud-based systems. The role combines hands-on technical leadership with mentoring, team building, recruiting, architecture, model optimization, and operational excellence. Responsibilities include developing intelligent systems, managing distributed ML infrastructure, deploying models with Kubernetes, collaborating across product and engineering teams, and advancing ML engineering practices.

Advance business continuity, disaster recovery, and operational resilience programs through business impact analyses, dependency mapping, plan quality assurance, scenario testing, data analytics, dashboard reporting, governance documentation, audit support, and continuous improvement. Partner with business, technology, and risk stakeholders to identify recovery gaps, assess operational dependencies, monitor resilience metrics, and strengthen readiness across banking and premium product operations.