Senior Lead Data Analyst
NerdWallet
AirflowPythonSQL
Senior Data Scientist
Penn Interactive
full-time
Posted on:
Location Type: Remote
Location: Remote • Pennsylvania • 🇺🇸 United States
Visit company websiteSalary
💰 $150,000 - $200,000 per year
Job Level
Senior
Tech Stack
AirflowPythonSpark
About the role
- Serve as a technical leader within the team, fostering a collaborative and innovative environment
- Partner with stakeholders to deeply identify business problems that can be solved through impactful personalization initiatives
- Utilize your mastery of recommender systems, two-tower models, and other advanced personalization techniques to architect, build and deploy high-impact solutions that strategically advance the ESPN Bet and theScore product strategies
- Take full ownership of critical components within data science projects, defining the roadmap and leading cross-functional teams
- Collaborate with Data Engineers and Machine Learning Engineers to guarantee seamless integration, deployment, and production readiness
- Contribute to the ongoing evolution of our data science infrastructure and champion best practices
- Drive Innovation by staying at the forefront of data science and machine learning trends
- Confidently present your solutions and strategic recommendations to diverse audiences, including senior leadership, using compelling narratives, insightful data visualizations, and a deep understanding of business implications to influence critical decision-making
- Other duties as required
Requirements
- Ideally 4+ years of industry experience (Data Scientist, ML Engineer, etc.)
- University degree in Computer Science, Mathematics, Statistics or related field
- Strong track record of designing, prototyping, scaling and deploying data science products to solve complex business challenges (with a focus on recommendation engines)
- Expert coding skills in general purpose languages like Python, and familiarity with robust software engineering principles
- Deep understanding of Machine Learning lifecycle, best practices, algorithms and domains
- Fundamental understanding of the data engineering practices around creation of data pipelines, processing data and storing data using technologies such as Spark
- Experience collaborating with and understanding the needs of stakeholders from a variety of business domains and ability to incorporate their expertise into the end state solution
- Demonstrated ability to take a product-oriented mindset in using conceptual and innovative thinking to develop and apply solutions taking into consideration the user experience
- Proven ability to communicate complex topics clearly and effectively to audiences of varying technical levels both in written and oral settings
- Experience with automation & orchestration tools such as Airflow, Dagster, DBT or Cron jobs.
- Knowledge of the sports betting industry is preferred, but not mandatory
Benefits
- Penn Interactive is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.Base pay is one part of the Total Rewards that Penn Interactive provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Penn Interactive provides best-in-class benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life.
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
recommender systemstwo-tower modelsdata sciencemachine learningPythondata pipelinesalgorithmsdata processingdata storagesoftware engineering
Soft skills
collaborationleadershipcommunicationproblem-solvinginnovationstakeholder engagementproduct-oriented mindsetconceptual thinkingnarrative presentationuser experience consideration
