Senior Data Science Engineer, Trading Intelligence

DraftKings; Boston (MA); Remote; USD 140,000 - 210,000; Full time

Job summary

DraftKings in Boston is hiring a Senior Data Science Engineer on our Trading Intelligence Team. You will develop advanced models and algorithms, analyze large datasets, and provide actionable insights to enhance our platform and business operations.

Lead data science projects from concept to deployment, collaborate with cross-functional teams, and mentor junior data scientists while embedding data-driven decision-making into trading processes.

Qualifications

• Experience leading data science projects from concept to deployment.
• Strong ML and statistical modeling background.
• Proficiency in Python or R and data manipulation/visualization tools.
• Ability to break down complex problems into executable tasks.
• Experience with automated trading or decision-making systems is a plus.
• Familiarity with Kubernetes, Kafka, Databricks is desirable.
• Bachelor's degree in CS, Statistics, Mathematics or a related field.

Responsibilities

• Lead data science projects from conception to deployment.
• Develop statistical models and ML algorithms to solve business problems.
• Collaborate with cross-functional teams to deploy data science solutions.
• Mentor junior data scientists.
• Communicate findings to stakeholders to drive data-driven decisions.
• Assist with adoption of data-driven strategies in trading processes.
• Contribute to design, development, testing of trading automation.

Skills

Data science

Machine learning

Python or R

Statistical modeling

Trading systems

Kubernetes

Kafka

Databricks

Experimentation

Team collaboration

Education

CS/Stats/Math degree

Tools

Kubernetes

Kafka

Databricks

Job description

DraftKings in Boston is hiring a Senior Data Science Engineer on our Trading Intelligence Team. You will develop advanced models and algorithms, analyze large datasets, and provide actionable insights to enhance our platform and business operations.

Lead data science projects from concept to deployment, collaborate with cross-functional teams, and mentor junior data scientists while embedding data-driven decision-making into trading processes.