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Staff Data Scientist

theScore is seeking a Staff Data Scientist specializing in Personalization to enhance user engagement and satisfaction through advanced data-driven solutions.

Skills

  • Expertise in data science principles and techniques
  • Strong coding skills in Python
  • Understanding of Machine Learning lifecycle
  • Experience with recommender systems
  • Familiarity with data engineering
  • Knowledge of automation tools

Responsibilities

  • Lead technical initiatives in data science projects
  • Collaborate with stakeholders to identify business problems
  • Architect and deploy personalization solutions
  • Oversee critical components of data science projects
  • Contribute to data science infrastructure and best practices
  • Present strategic recommendations to diverse audiences

Education

  • University degree in Computer Science, Mathematics, Statistics or related field

Benefits

  • Opportunity for remote work
  • Diverse work environment
  • Equal opportunity employer
  • Support for special accommodations
To read the complete job description, please click on the ‘Apply’ button

Average salary estimate

$125000 / YEARLY (est.)
min
max
$100000K
$150000K

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What You Should Know About Staff Data Scientist , Score Media and Gaming Inc.

Join theScore, a dynamic subsidiary of PENN Entertainment, as a Staff Data Scientist, specializing in Personalization, in our vibrant Toronto office! Imagine being at the forefront of sports engagement, where you can shape the experience of millions of fans who rely on our leading media app and cutting-edge sports betting platform. In this pivotal role, you'll harness your expertise in data science to design and implement personalization strategies that drastically enhance user engagement on the ESPN Bet platform. Your responsibilities will include collaborating with stakeholders to identify key business challenges and deploying sophisticated models that deliver timely, relevant content to our users. We’re looking for someone with a robust background in developing personalization engines and a passion for sports and esports. The ideal candidate will have 7+ years of experience in various data-centric roles, and be proficient in modeling techniques, coding in Python, and navigating the ML lifecycle. But beyond technical skills, we want a leader who can inspire and innovate, seamlessly integrate solutions, and communicate insights effectively to stakeholders. With a commitment to ongoing evolution in data science and an openness to collaboration, you will play a crucial role in shaping the future of theScore's products while enjoying the vibrant, fast-paced world of sports betting. If you’re ready to drive significant impact in an engaging environment, we’d love to hear from you!

Frequently Asked Questions (FAQs) for Staff Data Scientist Role at Score Media and Gaming Inc.
What does a Staff Data Scientist at theScore do?

A Staff Data Scientist at theScore is responsible for designing and implementing innovative personalization strategies that enhance user engagement. They leverage their expertise in data science and personalization engines to develop and deploy sophisticated models that deliver tailored content to users on the ESPN Bet platform.

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What qualifications are needed for the Staff Data Scientist position at theScore?

Ideal candidates for the Staff Data Scientist role at theScore should have a university degree in Computer Science, Mathematics, or Statistics, along with 7+ years of industry experience. Strong coding skills in Python, knowledge of machine learning principles, and experience with recommendation engines are crucial for success in this position.

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What is the work culture like in theStaff Data Scientist team at theScore?

The work culture within the Staff Data Scientist team at theScore is collaborative and innovative, encouraging team members to foster new ideas and share expertise. Team members are expected to take ownership of projects while working closely with stakeholders and other data professionals to drive impactful personalization initiatives.

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What kind of projects would a Staff Data Scientist at theScore be involved in?

As a Staff Data Scientist at theScore, you would engage in projects that aim to architect and deploy high-impact personalization solutions for the ESPN Bet platform, using advanced techniques like recommender systems and two-tower models while collaborating with other data professionals.

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Is a background in sports necessary for a Staff Data Scientist at theScore?

While a background in sports betting is preferred for the Staff Data Scientist position at theScore, it is not mandatory. However, having a genuine interest in professional sports, betting, and esports can enhance your contribution to the team.

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How can a Staff Data Scientist influence business decisions at theScore?

A Staff Data Scientist can influence business decisions at theScore by presenting compelling narratives and data visualizations to diverse audiences, including senior leadership, and providing insightful recommendations based on deep data analysis and understanding of user engagement trends.

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What technologies should a Staff Data Scientist at theScore be familiar with?

A Staff Data Scientist at theScore should be familiar with technologies related to the data science lifecycle, including data pipeline creation, Spark, and automation tools like Airflow and DBT. Additionally, expertise in software engineering principles is essential for developing scalable data science products.

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Common Interview Questions for Staff Data Scientist
What experience do you have with personalization engines?

In answering this question, highlight specific projects where you've designed, prototyped, or deployed personalization systems. Elaborate on the techniques you used and the impact these systems had on user engagement and satisfaction.

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Can you explain the machine learning lifecycle?

The machine learning lifecycle includes stages such as problem definition, data collection, data preparation, modeling, evaluation, deployment, and monitoring. Make sure to articulate your understanding of each stage and provide examples where you've implemented this process in past projects.

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How do you approach collaboration with stakeholders?

Effective collaboration with stakeholders involves understanding their needs, translating business problems into data science solutions, and maintaining open communication. Share specific experiences where your collaboration led to successful outcomes.

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What coding languages are you proficient in?

You should mention your proficiency in Python and any other relevant programming languages that you’ve used in data science. Provide examples of projects where you effectively applied these coding skills.

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Describe a significant data science project you led.

Discuss a project where you took ownership and led its execution. Outline the problem, your approach, the results, and any lessons learned. Highlight contributions made in terms of personalization or user engagement.

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What methods do you use for model evaluation?

When discussing model evaluation, mention metrics like accuracy, precision, recall, and AUC. Describe how you apply these methods to ensure that models meet business requirements and improve user experiences.

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How do you ensure the scalability of your data science solutions?

Explain your approach to designing scalable solutions, whether it involves selecting the right architectures, optimizing code, or collaborating with data engineers to ensure robust data pipelines.

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What trends in data science do you find most exciting?

Share your personal interests in current data science trends, such as advancements in deep learning, ethical AI, or emerging personalization techniques. Reflect on how staying updated can influence your work as a Staff Data Scientist.

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How do you handle setbacks or project failures?

Describe your proactive approach to feedback and learning. Highlight how you analyze failures to adapt strategies and improve future project outcomes.

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What is your experience with data visualization tools?

Talk about your experience with tools like Tableau, Matplotlib, or other data visualization platforms. Provide examples where your visual representations helped communicate complex data insights effectively.

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theScore empowers millions of sports fans through its digital media and sports betting products. Its media app 'theScore' is one of the most popular in North America, delivering fans highly personalized live scores, news, stats, and betting inform...

26 jobs
MATCH
Calculating your matching score...
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
SALARY RANGE
$100,000/yr - $150,000/yr
EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
November 29, 2024

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