Analyst, Audit Data Analytics & Insights

Fidelity Investments • Smithfield, RI

2d • Onsite

About The Position

Note: Fidelity is not providing immigration sponsorship for this position Are you interested in applying your analytics skills while utilizing knowledge about data sources from across Fidelity’s varied businesses and technologies? Do you want to work closely with business partners to deliver new insights, develop automated workflows, and improve their decision-making capabilities? If so, join our team and embrace this exciting and unique opportunity to learn about and interact with data from across the enterprise, with some examples including analyzing detailed client and customer data from Fidelity’s recordkeeping systems, understanding how investment products are built, and developing analytics about new products and offerings (such as cryptocurrency, new trading apps, etc.). The Role As an Analyst, Data Analytics and Insights in Fidelity’s Legal, Risk, and Compliance (LRC) organization, you will play a key role working closely with members of Fidelity’s Audit team (as well as Risk, Compliance, Legal and GSI), customer-facing business units, and key data providers to find opportunities where data can provide insight into risk. You will participate in all phases of a data analytics project lifecycle – from framing the business question/hypothesis, identifying the appropriate data sources, sourcing the relevant data, performing sophisticated analytics, and reporting on the results. You will use data to answer ad-hoc questions and develop data-centric solutions that will be deployed to users throughout the firm.

Requirements

• Bachelor's or Master's degree, ideally in an analytics or technical field
• 2 to 3 years’ experience working with data in relational databases (SQL Server, Oracle, DB2, Snowflake).
• 1 year of software development experience using languages such as COBOL, Java, .NET, Python, R, etc.
• Experience performing data exploration, building business intelligence reports and developing visualizations (using OBIEE, Power BI, or Tableau).
• Familiarity with cloud processing and data storage environments (AWS, Azure, other SAAS solutions).
• A solid understanding of ETL tools and processes (Alteryx, Informatica, SSIS, etc.).
• Skilled at effectively defining use cases and have proven analytical/problem-solving skills with capability to determine solutions to unusual and complex problems.
• Proven track record communicating insights in a simple, clear, and actionable way.
• Inherently good attention to detail, collaborative, and ability to multi-task and adapt quickly in a fast-paced environment.
• Knowledge of the financial services industry, particularly in the workplace savings, retail, and institutional businesses.
• A passionate can-do attitude to your work.
• Committed to cross-functional teamwork to achieve the best results for Fidelity and for our customers.
• Natural intellectual curiosity, initiative, and love for learning new skills and capabilities.
• Outstanding interpersonal/communication skills and a willingness to participate in Scrum teams.
• Experience in an Audit, Risk, Compliance or Security function.

Responsibilities

• Participate in all phases of a data analytics project lifecycle – from framing the business question/hypothesis, identifying the appropriate data sources, sourcing the relevant data, performing sophisticated analytics, and reporting on the results.
• Use data to answer ad-hoc questions and develop data-centric solutions that will be deployed to users throughout the firm.
• Continuously improving data analytics and insights capabilities and spreading that knowledge and expertise throughout the organization.
• Delivering data-driven and useful insights to enable objective and informed decisions.
• Developing new solutions and tools that risk professionals will use to proactively identify risk across the firm.
• Participating on audits, investigations, or other special projects that benefit from your subject matter expertise.
• Working across LRC teams to find opportunities where data analytics, automation, or machine learning can reduce manual processing and drive scale and efficiency.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Associate degree