Job Description

As a valued colleague on our team, you will contribute to the overall direction of analytical activities, and data infrastructure and database maintenance, as well as coordinating business unit operational activities with the help of peers and staff managers.

THE IMPACT YOU WILL MAKE

You will use moderately complex techniques to produce insights, new product or change recommendations, process improvement or automation, operational excellence, and predictive modeling. You will use data mining and data visualization, analysis methods, be adept with common large data processing techniques, computational programing capabilities, practical problem-solving skills, and have an ability to articulate solutions to non-technical consumers or partners. As a senior associate, you will partner with business, operations, technology, data engineering and management teams, and apply data mining and visualization techniques for insightful solutions.

The Senior Data Analyst (Tableau, Flask, Python & Operational Risk) role will offer you the flexibility to make each day your own, while working alongside people who care so that you can deliver on the following responsibilities:

Collaborate with product and/or business owners, business operations, technology, data engineers, and platform teams to understand business needs and current capabilities, data availability, and alternative uses.
Implement new statistical modeling capabilities to increase operational excellence and productivity.
Apply descriptive, predictive and prescriptive analytic capabilities to enhance the delivery of business insights & solutions, and support the integration of data and statistical models or algorithms.
Apply industry practices in research and testing, development, deployment, and maintenance of solutions to increase operational .
Design new modeling applications to support operations process improvement, automation, risk measurement, decision making, and business performance.
Design data visualizations, technical documentation, and non-technical presentation materials to communicate complex ideas and solutions to business partners.
Identify business needs for analytic support, testing activities, and quantitative analysis.
Monitor and report on analytic activities and evaluate use of testing and modeling techniques.
Translate data outputs to customers, business partners, and key stakeholders.
Contribute to building predictive data models and machine learning tools to help fuel Fannie Mae's innovation and impact.

Qualifications

THE EXPERIENCE YOU BRING TO THE TEAM

Minimum Required Experiences

2 years

Desired Experiences

Master's degree in a quantitative field highly preferred 
4 years of experience working in an analytical function
Strong analytical skills with proficiency in Tableau, Python and SQL
Experience with Operational Risk
Experience with Flask
Experience working with large, complex data sets and applying statistical models
Able to translate business questions into analytical plans and effectively communicate findings to technical and nontechnical audiences
Genuine interest in applying data to build support for operations and technology
Enjoy working in a fast-paced environment as part of a cross-functional team

Skills

Business Insight including advising, designing business models, interpreting customer and market insights, forecasting, benchmarking, etc.
Experience in the process of analyzing data to identify trends or relationships to inform conclusions about the data
Experience gathering accurate information to explain concepts and answer critical questions
Ability to frame ideas as systems and analyzing the inputs, outputs, and process
Skilled in the graphical representation of information in the form of a charts, diagrams, pictures, and dashboards with programs and tools such as Excel, Tableau, or Power BI
Operational Excellence including improving and overseeing operations
Focused experience in artificial intelligence (AI), including machine learning and natural language processing (NLP)
Expertise in using statistical methods, including: developing and testing hypotheses, using experimental design, and running linear and logistic regressions

Tools

Skilled in AWS Machine Learning tools such as SageMaker, Lex, Polly, or Forecast
Skilled in Python object-oriented programming
Skilled in Tableau
Skilled in Alteryx for data analytics applications
Skilled in SQL