Director, Research and Analytics, CKSI --Model Governance
You have unique skills and have mastered building and applying models to real-world business problems, but you are looking for an opportunity to be hands-on while helping evaluate and shaping how a company uses cutting edge statistical, machine learning, and deep learning algorithms day-to-day to drive strategic decisions. At Fidelity, we are making tremendous strides in leveraging a vast array of models to inform our business and improve our customers' experience. We are looking for a special breed of people like you - part data scientist, part model validator, and all about ensuring we improve the experience for our millions of customers - to help us develop and apply sound measurement, validation and governance practices our modeling efforts across the business.
We want you to not only help us with the challenges we face today, but harness your energy as a collaborative self-starter to take risks and be a thought leader to develop with new ways to track model performance, data anomalies, and identify potential problems before they are readily apparent. You will be working with and supported by a world class team of colleagues and leaders who will empower you to be at the forefront of evaluating, validating, and tracking model performance on our Model Governance squad in the Personal Investing division. We are obsessed with being an industry leader at leveraging data and models to help our customers, so come join us and be part of the exciting transformation that is happening at Fidelity.
The Expertise We're Looking For
Master's level or higher degree in computational, predictive or business analytics, computer science, information and data science, operations research, statistics, or related field.
5 years' experience building, testing, and applying models to business problems using a wide array of statistical (including Bayesian), machine learning, and/or deep learning algorithms, preferably in an open source environment.
2-5 years' experience working with model measurement, validation, and governance, along with a natural curiosity and passion for understand how models work and what drives their performance.
Strong background in statistics, quantitative modeling, data engineering and automation, and mastery of either R or Python, with SQL experience.
Experience working with machine learning in a cloud environment, specifically with AWS Sagemaker, is preferred.
Similarly, familiarity with deep learning and related toolkits such as TensorFlow, PyTorch or Theano is also preferred.
Ability to work with analytic and visualization tools, including Qlik, Tableau, D3.js, or R-Shiny, and leverage them to build and design visualizations that transform data into actionable insight.
Naturally collaborative with experience working in an Agile environment, including with remote teams, both on and off shore.
Excellent written, oral communication, project management and presentation skills, and the ability to present complex data and statistics in a simple and clear way.
Proficient in PowerPoint and other Microsoft applications.
Demonstrated track record of customer-focused engagement and collaboration across an organization is required.
The Purpose of Your Role
Fidelity is looking for a leader who is passionate about modeling to be a thoughtful and collaborative team member, helping develop and implement model validation and governance standards across the Personal Investing (PI) division of Fidelity. This role has a wide range of responsibilities, including developing model governance standards, designing and evaluating methods for model validation, and accelerating the model governance process through cloud-ready automation. This position will have additional responsibilities to develop and implement algorithms that detect anomalies in model inputs so a hands-on experience in developing and evaluating models is required. You will also play a central roll in Fidelity's effort to migrate data and analytics to the cloud, and leverage emerging open source and commercial capabilities in the areas of model governance.
The Skills You Bring
- You bring passion to your work to inspire and motivate your team, including teaching and coaching others.
- You are committed to cross-functional collaboration to achieve the best results for Fidelity, working across the business to build partnerships and ensure consistency in governance.
- You demonstrate versatile mix of theoretical knowledge, practical application, and expert coding skills, always focusing on the business use cases and customer needs.
- You are intellectually curious, taking the initiative to learn new skills and share that knowledge with others, and working to understand why models perform as they do.
- You bring a data-driven approach to decision making so that you can inform model owners with facts not just theories.
- You have extensive experience in partnering with key stakeholders to understand the business justification for a model and how the varying levels of performance translates into results and impact customer experiences.
The Value You Deliver
You will be working on a squad to develop standards, methods, and tools for model validation and governance and applying them across the Personal Investing business unit to track model performance to inform Fidelity's senior executive decision making, shaping the direction of the company.
Working across the Personal Investing division and with our AI Center of Excellence, you will determine when a model's performance degrades and the potential impact on our business and customers so we can mitigate impact.
You will identify, test and evaluate new software and tools that bring value to Fidelity and help validate and govern existing and future models.
Your experience in data engineering, automation, and working in the cloud will drive the transition of our governance efforts as we increasingly become more cloud-centric.
How Your Work Impacts the Organization
Fidelity places a strong emphasis on making data-driven decisions to drive growth and profitability. You will play a critical role in helping us evaluate how our models are performing and implementing sound governance that helps statistical, machine learning, deep learning algorithms reach their full potential and drive the organization's strategic business decisions and customer experience.