Lead Data Science Engineer

Key Skills

Data science techniques, DevOps, Django, Docker, Effective communication skills, Flask, Grafana, HTTP acceleration, Leadership Skill, Machine learning techniques, MLOps tools, Python Programming, Streaming APIs

Job Description

The Crown Is Yours

​Our team comprises sports modelling experts and data science technologists, coming together to develop innovative DS products that deliver incremental value on the Sportsbook platform at DraftKings.

As part of this role, you will be a creative thinker, utilizing data, machine learning, and software development skills to craft high-impact best-in-class sports models that grow the business.

What you’ll do as a Lead Data Science Engineer

• Research and implement DS applications in Python

• Create statistical and machine learning models and integrate them into DS applications

• Work with and help develop our MLOps pipeline

• Data engineering of data assets to assist in DS application development

• Writing production quality code to deploy and run models in a sportsbook

• Create automatic tests to ensure accuracy and reliability of DS applications

• Collaborate closely with product, developers, QAs and delivery leads to move projects from ideation to development and deployment

• Test that data flows work as expected and that DS applications are well integrated in larger business context

• Build advanced analytics tools for sportsbook product teams

• Coach and support more junior data scientists within the team

What you’ll bring

• Ideally, you have experience as the expert on a data science team where you were responsible for all aspects of data science technical projects, including development and deployment, and then monitoring of how those applications perform in production

• PhD, Masters or Bachelor’s degree in STEM fields

• Highly proficient in at least one programming language, ideally Python, with a strong understanding of object-oriented programming principles

• Understanding of different database technologies, including relational and non-relational databases

• Experience implementing ML automation, MLOps principles and related tools

• AWS experience will be considered an asset

• Experience with typical DevOps flows, such as containerisation (e.g. Docker) and monitoring (e.g. ELK, Grafana)

• Experience with Kubernetes and Kafka are very desirable

• Knowledge of web frameworks (e.g. Flask, Django) and HTTP APIs desirable

• Keen interest in sports

• Understanding of Sportsbook products will be considered an asset

• Experience leading and coaching other data scientists

• Excellent communication & organizations skills with the ability to articulate key business information quickly and effectively