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State Street
State Street

Leading company in the financial services industry

Data Analytics & Management, AVP

职能数据分析
级别中级
地点Hangzhou, China
方式现场办公
类型全职
发布1周前
立即申请

About the job

The Finance Data and AI Office (DART) delivers trusted data, analytics, and AI enabled solutions across Finance, Risk, and Treasury. This role sits within the Automation, Analytics & AI pillar and focuses on building practical, scalable solutions that address real finance challenges end to end—from problem framing and solution design through deployment and adoption—including data governance and internal control capabilities that align to regulatory expectations and standards.

Who we are looking for

The ideal candidate combines strong analytical thinking with business curiosity and judgment and can thoughtfully apply emerging AI capabilities and low‑code/no‑code tools to build data solutions with tangible Finance outcomes—improving insight quality, controls, efficiency, and decision‑making.

What you will be responsible for:

Build Agentic AI & Copilot Solutions for Finance:

  • Design and deliver agent‑based workflows that can plan, reason, and execute tasks across finance processes (with appropriate human oversight and controls).
  • Implement solutions that use LLM copilots for finance narratives, variance explanations, exception triage, and root‑cause analysis
  • Combine AI reasoning with deterministic logic (rules, thresholds, accounting constraints, materiality) to ensure reliability in controlled environments

Prompt Engineering & Context Design (Finance‑Grade)

  • Create and refine prompts grounded in finance context (e.g., P&L, cost centers, accounting rules, materiality thresholds) and structure outputs for decision‑making.
  • Build reusable prompt patterns, evaluation approaches, and guardrails to reduce hallucinations and increase consistency.

Apply Data Science Where It Matters:

  • Use analytics and data science methods (e.g., anomaly detection, classification, forecasting support, explainability) to strengthen finance insight and controls.
  • Analyze large, complex datasets to identify breaks, drivers, trends, and actionable signals relevant to Finance operations and reporting.

Enable AI Using No‑Code / Low‑Code Platforms

  • Use no‑code and low‑code tools (e.g., Alteryx, Power BI, Power Platform or similar) to:
  • Operationalize AI outputs into finance workflows
  • Orchestrate AI‑driven steps alongside rules‑based logic
  • Surface AI‑generated insights, exceptions, and narratives to end users

Responsible AI & Controls‑Aware Delivery

  • Ensure solutions are explainable, auditable, and aligned with governance expectations
  • Validate AI outputs against financial data and business logic; design monitoring to maintain quality over time.

Regulatory Alignment, Data Governance & Controls

  • Contribute to BCBS 239 and broader regulatory aligned outcomes by improving traceability, accuracy, completeness, timeliness, and evidencing for critical finance/risk data used in aggregation and reporting
  • Ensure solutions delivered are consistent with broader regulatory expectations and embed appropriate data governance and controls from design through production

Skills and experience needed:

  • Bachelor’s degree in AI, Data Analytics, Computer Science, Engineering, or a related field.

  • 3-5 years of experience in emerging AI technologies, data science, analytics, automation (financial services preferred)

  • Strong analytical and problem‑solving skills

  • Proficiency in SQL and Python

  • Familiar with data warehousing, data modelling, ETL concepts

  • Exposure to automation tools (e.g., low‑code platforms, RPA, workflow tools).

  • Understanding of Finance, Risk and/or Treasury business processes

  • Knowledge of data governance, data quality, and regulatory compliance concepts (e.g., BCBS 239 principles)

  • Strong written and verbal communication skills

  • Knowledge of the below tools is preferrable

  • Microsoft Co-pilot Studio

  • Microsoft 365 Co-pilot

  • Databricks

  • Anthropic/Claude

  • Alteryx

  • Microsoft Fabric

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

Discover more information on jobs at StateStreet.com/careers

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关于State Street

State Street

State Street Corporation is an American multinational financial services and bank holding company headquartered at One Congress Street in Boston. It is the second-oldest continuously operating U.S. bank, tracing its roots to Union Bank, chartered in 1792.

10,001+

员工数

Boston

总部位置

$55B

企业估值

评价

10条评价

3.7

10条评价

工作生活平衡

3.2

薪酬

4.0

企业文化

3.8

职业发展

3.4

管理层

2.8

68%

推荐率

优点

Supportive colleagues and team culture

Good benefits and retirement plans

Learning and advancement opportunities

缺点

Heavy workload and overtime expectations

Poor management direction and support

High stress and fast-paced environment

薪资范围

101个数据点

Junior/L3

Mid/L4

Junior/L3 · Business Analyst

2份报告

$134,560

年薪总额

基本工资

$117,009

股票

-

奖金

-

$127,061

$142,060

面试评价

5条评价

难度

2.6

/ 5

时长

21-35周

录用率

20%

体验

正面 20%

中性 60%

负面 20%

面试流程

1

Application Review

2

Recruiter Screen

3

Phone Interview

4

Technical/Hiring Manager Interview

5

Final Interview/Offer Stage

常见问题

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit