Investment Data Analyst

Fidelity Investments•Greenwood Village, CO

1d•Hybrid

About The Position

The Investment Data Analyst role will be responsible for providing scalable, timely, easily consumable and good quality data for consumption by SAI led products and functions. This position will help drive and define strategy for data analysis, management, acquisition, and distribution. Working closely with SAI business as well as technology partners, the position will participate on projects of various size and complexity, including product/platform development and enhancement.

Requirements

2 plus years or more in a data intensive, hands on environment, preferably within investment management or technology industries!
Bachelor's Degree required (completed or in progress)
Introductory Fidelity experience; experience with system development projects, business analysis, and data analysis.
Basic knowledge of asset allocation investment products, Performance, Attribution, Fixed Income and Risk related experience.
Good data querying skills using SQL, TOAD, Tableau, Excel, or any other applications.
Prior Experience with Reporting and Visualization Tools like Tableau, Spotfire, Alteryx or other BI, Data Prep, Blending etc.
Basic understanding of AI/ML concepts, R, Python or Scala is preferred.
Understanding of MS Excel (macros, VLOOKUP’s, VBA) and PowerPoint
Basic project management skills and ability to prioritize multiple work streams, track progress and effectively communicate and handle expectations.
Basic analytical skills and business judgment.
Intellectual curiosity and commitment to continuous improvement.

Nice To Haves

Interest in CFA / CAIA / Financial Certification is good to have but not required.

Responsibilities

Develop and implement a repeatable process aimed at streamlining the data sourcing, aggregation, quality & distribution
Research, recommend and implement automation, digitization, and new scalable solutions for distributing data.
Partner with members of business and technology teams to develop Project and Execution Plans, establish agreed-upon milestones and raise issues, as necessary.
Ensure timely production and meet calendar deadlines.
Participate in other data-related efforts to support ad-hoc reporting and analysis.
Operationally monitor, govern, and triage data issues arising from nightly batch or real time data sourcing, working with internal and external partners and vendors.