ABOUT FANDUEL

FanDuel Group ("FanDuel") is an innovative sports-tech entertainment company that is changing the way consumers engage with their favorite sports, teams, and leagues. The premier gaming destination in the United States, FanDuel consists of a portfolio of leading brands across gaming, sports betting, daily fantasy sports, advance-deposit wagering, and TV/media.
FanDuel has a presence across all 50 states with approximately 17 million customers and 28 retail locations. FanDuel is based in New York with offices in New Jersey , Georgia, California, Oregon, Canada and Scotland.
Its networks FanDuel TV and FanDuel+ are broadly distributed on linear cable television and through its relationships with leading direct-to-consumer over-the-top platforms.
FanDuel Group is a subsidiary of Flutter Entertainment plc, the world’s largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

THE POSITION

Our roster has an opening with your name on it
At FanDuel, data is the heartbeat of our organization. As an ML Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will be asked to provide our business with insight and our customers with world-class personalized experiences. Every click our users make, every bet, every touchdown, every fumble, and every play is fair game for us to turn into a stream of knowledge. Your expertise will be used here to make better and faster decisions – outpacing our competition.
Collaboration is at the core of your role. You’ll be the linchpin between engineering teams working downstream to build out our online application and upstream to land necessary data for feature engineering. You’ll also be working with Data Scientists and Analysts to productionize, analyze, and validate AI powered insights. You will be asked to help organize, model, and present our data as a coherent product and offer it to our stakeholders, providing a common information framework that allows FanDuel to intelligently react to what is happening on the field and in the marketplace.
We are looking for ML Engineers of all skill levels or experienced engineers from other disciplines who may be looking to make the move to a big data environment. If this describes you, read on – we want to hear from you!

THE GAME PLAN

Everyone on our team has a part to play

• Building multi-layer serving architectures for ML models
• Business intelligence tools (e.g., Tableau, Knime, Looker)
• Data security and privacy (e.g. GDPR, CPP)
• Data governance and data testing frameworks.
• Continuous integration and delivery of production data products
• An inclusive culture that expects excellence and priorities your growth as an engineer and your well-being as a person
• Advance your career within well-defined, skill-based tracks, either as an individual contributor or as a manager – both providing equal opportunities for compensation and advancement
• Apply your experience and intellect as part of an autonomous team with end-to-end ownership of key components of our data architecture.
• Serve as a mentor to more junior engineers not only in cultivating craftsmanship but also in achieving operational excellence – system reliability, automation, data quality, and cost-efficiency.

ML engineering is a rapidly changing field – most of all, we’re looking for someone who enjoys experimenting, keeping their finger on the pulse of current data engineering tools, and always thinking about how to do something better.

THE STATS

What we’re looking for in our next teammate

• 2-3+ years of relevant experience developing code in one or more core programming languages (Python, Java, etc.)
• 1-2+ Years of experience in deploying ML models under the constraints of scalability, correctness, and maintainability.
• Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, etc.)
• 3+ Years of experience designing and building various software architecture.
• Deep understanding and knowledge of data structures and software engineering principles
• 1-2+ Years of experience demonstrating technical leadership working with teams, owning projects, defining, and setting technical direction for projects.
• Experience with one or more relevant tools (Flink, Spark, Sqoop, Flume, Kafka, Amazon Kinesis)
• Ability to share findings in easy to consume formats, whether that is through dashboards or data modeling.
• Conduct regular design process reviews and ensure development standards within the team.
• Working with leadership to drive adoption of ML solutions to product engineering teams.
• Experience working in a cloud environment such as AWS, GCP, Azure.
• Experience with Databricks is a plus, their unity catalog, another plus.
• Designing and building data pipelines for production level ML infrastructure.
• Motivate junior engineers on best practices and latest industry design patterns.

LI-Hybri