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Pincipal Data Scientist

Are you interested in architecting the future application of data science to live games, content platforms and interactive entertainment? Join us at Series AI, where we are pioneering new frontiers in the gaming industry by leveraging sophisticated data solutions and cutting-edge technology!

We are seeking an innovative Principal Data Scientist, AI/ML to lead our data science initiatives and architect & build advanced data systems. This role is perfect for a scrappy, visionary candidate who thrives on using ML/AI tools in novel and impactful ways – educating others in how to leverage such tools along the way.

Key Responsibilities:

  • Develop and implement the strategic vision for data science and ML/AI solutions across our products.

  • Architect scalable data systems to support advanced ML/AI functionalities in gaming and interactive platforms.

  • Implement best practices and workflows to develop innovative machine learning models and algorithms that enhance user experiences.

  • Collaborate with product, engineering, and design teams to integrate ML/AI solutions seamlessly into our products.

  • Stay up-to-date with the latest trends and advancements in ML/AI and data science, applying them to keep our offerings cutting-edge.

  • Communicate complex data concepts and strategies to stakeholders and non-technical audiences.

Qualifications:

  • Master’s or PhD in Data Science, Computer Science, Statistics, ML/AI, or a related field AND/OR 5-7+ years of experience in data science and machine learning, with at least 3 years in a senior role. 

  • Proven track record of architecting and deploying scalable data systems and ML/AI-driven solutions.

  • Strong experience with ML/AI frameworks such as scikit-learn, TensorFlow, PyTorch, MLFLow, and other machine learning tools.

  • Solid understanding of data engineering concepts - ETL practices, data pipelines, and distributed data processing - and streaming solutions (Kafka, Flink).

  • Familiarity with the full MLOps lifecycle - version control, model deployment, evaluation, performance monitoring, CI/CD.

  • Proficiency in programming languages like Python, R, or Java.

  • Excellent problem-solving skills and ability to work in a fast-paced, dynamic environment.

  • Exceptional communication and collaboration abilities.

Preferred Qualifications:

  • Ability to rapidly prototype, evaluate, and iterate to tackle ambiguous or novel challenges.

  • Experience with 0-to-1 development of personalized recommendation systems, user behavior modeling, real-time feedback loops, and reinforcement learning a plus.

  • Experience with early-stage or rapidly growing companies or gaming companies is a plus.

  • Leadership skills with a track record of mentoring and growing high-performance teams.

  • Experience with cloud services for AI and data processing (AWS, Google Cloud, Azure, Databricks).

At Series AI, we cherish diversity and strive to create an inclusive environment for all employees. We are an equal opportunity employer and welcome individuals from all backgrounds. If you are motivated by the challenge of pioneering data-driven innovations in the gaming landscape and enhancing operational intelligence, we eagerly await your application.

Embark on your next professional adventure and apply today to be a part of our trailblazing team!

Series Entertainment embraces diversity and is committed to creating an inclusive environment for all employees. We are an equal opportunity employer, welcoming individuals from various backgrounds, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status. If you are driven by the challenge of enhancing development operations and want to impact the future of gaming technology, we want to hear from you!

Take the next step in your career and apply to be part of our cutting-edge team today!

Average salary estimate

$150000 / YEARLY (est.)
min
max
$120000K
$180000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Pincipal Data Scientist, Series Entertainment

Are you ready to take a leap into the future of gaming technology? Join Series AI as our Principal Data Scientist and be at the forefront of innovating how we use data science in live games and interactive content! Here at Series AI, we're driven by a passion for pioneering data-driven solutions that reshape user experiences and redefine the gaming landscape. As our Principal Data Scientist, you will lead the charge in architecting advanced data systems and implementing machine learning solutions that will impact how players engage with our products. Imagine developing strategies for ML/AI that not only enhance our offerings but also inspire your colleagues to think outside the box. You'll collaborate with talented professionals across product, engineering, and design teams, ensuring that ML/AI integrations are seamless and effective. Staying abreast of the latest trends in the ML/AI sphere will be crucial as you adopt new technologies and methodologies to keep our projects cutting-edge. With a Master’s or PhD in a relevant field and several years in data science under your belt, you'll have the expertise to deploy scalable solutions successfully. Join us if you're ready to innovate in a dynamic environment, share your knowledge with a diverse team, and make your mark on the future of the gaming industry. Apply now and let's embark on this exciting journey together!

Frequently Asked Questions (FAQs) for Pincipal Data Scientist Role at Series Entertainment
What responsibilities does a Principal Data Scientist at Series AI have?

The Principal Data Scientist at Series AI is responsible for developing the strategic vision for data science and machine learning solutions, architecting scalable data systems for gaming, implementing best practices for ML model development, and collaborating with various teams for smooth integration of ML/AI functionalities.

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What qualifications do I need to apply for the Principal Data Scientist position at Series AI?

To apply for the Principal Data Scientist role at Series AI, you'll need a Master’s or PhD in Data Science, Computer Science, or related field, coupled with 5-7 years of relevant experience in data science and machine learning, including at least 3 years in a senior role.

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What technologies should a Principal Data Scientist at Series AI be familiar with?

Candidates for the Principal Data Scientist position at Series AI should be proficient with ML/AI frameworks like TensorFlow and PyTorch, have a solid understanding of data engineering concepts, and be familiar with programming languages such as Python, R, or Java, as well as cloud services like AWS or Google Cloud.

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What is the work environment like for a Principal Data Scientist at Series AI?

The work environment for a Principal Data Scientist at Series AI is dynamic and collaborative, fostering innovation and creativity. You'll be part of a diverse team that values learning, encourages mentorship, and supports you in staying updated on the latest trends in ML/AI.

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How does Series AI value diversity in the workplace for the Principal Data Scientist role?

Series AI is committed to creating an inclusive environment for all employees, emphasizing diversity in hiring and fostering a culture that welcomes backgrounds from various demographics and experiences, which enhances creativity and innovation in our data science initiatives.

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Common Interview Questions for Pincipal Data Scientist
Can you describe your experience with machine learning frameworks?

When answering this question, highlight specific frameworks like TensorFlow or PyTorch that you've worked with, elaborating on projects you've undertaken using these tools and any challenges you've faced during implementation.

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How do you approach architecting scalable data systems?

Discuss your understanding of data engineering concepts, including ETL processes and data pipelines. Provide examples of your previous projects where scalability was a key consideration, focusing on your problem-solving strategies.

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What methods do you use to stay updated on ML/AI trends?

You can outline your routine for professional development, mentioning resources such as academic papers, industry conferences, workshops, and online forums or courses that help you stay informed about the latest advancements in ML/AI.

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Can you give an example of a successful ML/AI project you led?

Share a detailed example of an ML project, discussing the goals, the methodologies you employed, the technologies used, and the results that were achieved, emphasizing your leadership role in driving the project to success.

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How would you communicate complex data concepts to non-technical stakeholders?

Emphasize your communication skills and your approach to simplifying complex topics. Provide examples of how you've effectively presented data concepts in a way that is accessible to stakeholders from various backgrounds.

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What are some best practices for developing machine learning models?

Discuss key best practices such as thorough data preprocessing, model validation techniques, performance monitoring, and iteration based on feedback, highlighting your own experiences in implementing these practices.

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Describe your experience with data pipelines and distributed data processing.

Explain your familiarity with data pipelines, mentioning tools you've used and the rationale behind your choices. Share experiences in distributed processing and how it contributes to scalability and efficiency.

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What programming languages are you most proficient in?

Mention the programming languages relevant to the role, such as Python or R, and provide examples of how you've used them in data science projects, including specific functions or libraries that demonstrate your proficiency.

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How do you handle working in a fast-paced, dynamic environment?

Reflect on your adaptability and your strategies for managing time and priorities in a dynamic work setting. Provide examples from previous roles where you thrived under pressure or adapted to rapid changes.

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What experience do you have with the MLOps lifecycle?

Discuss your understanding of the MLOps lifecycle, including version control, model deployment, and performance monitoring. Provide examples of how you've applied these concepts in past projects to ensure robust ML pipeline management.

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Photo of the Rise User
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)
MATCH
VIEW MATCH
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
No info
HQ LOCATION
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EMPLOYMENT TYPE
Full-time, on-site
DATE POSTED
April 10, 2025

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