State Street

State Street

Alpha Data Services – EDM Implementation Support (Trading Data: Security Master, Reference Data, Transactions

Clifton, New Jersey

Sponsorship not specified$90k-$158kDetected 5 days ago
PythonSQLData AnalysisData ScienceStakeholder ManagementCadenceCommunicationProblem Solving

About the role

  • This role is critical in ensuring the integrity, accuracy, and availability of data used across investment, risk, compliance, and client reporting functions.
  • Salary Range: $90,000 - $157,500 Annual The range quoted above applies to the role in the primary location specified.
  • If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

Responsibilities

  • Document requirements from the implementations which are accepted by the Practice leads as core enhancements
  • Own the implementation documentation around EDM, basecamp standards, operational UI configurations and look for ways to mature these
  • Manage and maintain reference and market data mappings for sources into EDM (e.g., securities, benchmarks, pricing).
  • Develop and maintain data mapping logic across systems and data sources.
  • Use SQL and programming tools to transform, validate, and reconcile data across platforms to ensure the platform is performing as expected
  • Work with eh insights & Analytics teams to mature and maintain dashboards and reports to track data availability metrics with regular cadence with End ot end test teams to ensure they are leveraging them
  • Provide support to client EDM Professional Services teams and Model office teams to ensure Model office is tested and managed
  • Liaise with internal stakeholders to understand data requirements and deliver solutions.
  • Support timely delivery of solution and change initiatives for our clients with accurate and timely data.
  • Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability.

Skills

  • Excellent analytical and problem-solving skills.
  • Experienced working Order Management systems gained from AIM, Charles River or Alladin
  • Strong attention to detail and commitment to data accuracy.
  • Effective communication and stakeholder management abilities.
  • Proactive mindset with a continuous improvement approach.
  • Experience across the full data science project lifecycle
  • Bachelor's degree in Finance, Economics, Computer Science, Data Science, or a related field.
  • Experience in data analysis or data management within asset management or financial services.
  • Experience with data management platforms and market data providers (e.g., Bloomberg, Refinitiv).
  • Knowledge of data governance frameworks and regulatory requirements (e.g., MiFID II, ESG reporting) is a plus.
  • Strong understanding of financial instruments (equities, fixed income, derivatives).
  • Experience with SQL, Python, R, or similar languages for data transformation and automation.

Compensation

  • $90,000 - $157,500 Annual
  • incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans)

Benefits

  • Education & Preferred Qualifications
  • Employees are eligible to participate in State Street's comprehensive benefits program, which includes: our retirement savings plan (401K) with company match
  • insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages
  • paid-time off including vacation, sick leave, short term disability, and family care responsibilities

Company info

  • Ability to work independently and as part of a cross-functional team.

Visa & Work Authorization

  • gin, 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 a

This listing is sourced directly from State Street's careers page and normalized into a canonical job model.