Role in brief
Chess.com is looking for a Senior Data Science Manager to lead data science initiatives, develop algorithms, and improve user experience. This role involves managing a small team and collaborating on product vision. Candidates with strong Python, SQL, and machine learning skills, who are also familiar with chess, should consider applying.
About the role
This role involves leading significant data science projects for Chess.com, focusing on both product data science and fair play. The work includes creating new algorithms, models, and data-driven features that directly enhance the user experience. Success in this position means delivering innovative solutions that improve the platform's functionality and fairness.
The Senior Manager will be responsible for designing and deploying creative heuristics, algorithms, and models. This requires a deep understanding of machine learning fundamentals and the ability to translate complex data insights into actionable product improvements. The role also involves close collaboration with various teams across the company to align data science efforts with the overall product vision and execution strategy.
A key aspect of this position is managing a small team of data scientists, providing guidance and mentorship. The company operates in a fully remote environment, emphasizing clear and frequent communication. Candidates should be comfortable with agentic workflows and tools, and possess proven ability to articulate findings effectively to diverse audiences.
The salary for this full-time role ranges from $115,000 to $195,500 annually.
Skills that matter here
- Python: This role requires strong Python skills for developing algorithms, models, and data-powered features.
- SQL: Strong SQL skills are needed to manage and analyze data for various data science projects.
- BigQuery: Familiarity with BigQuery will be used for data storage and querying within the Google Cloud Platform environment.
- GCP: Experience with Google Cloud Platform indicates the infrastructure used for data science operations.
- machine learning: Solid machine learning fundamentals are essential for creating and deploying novel algorithms and models.
Who this role suits
- A person who thrives on leading complex data science initiatives and enjoys seeing their work directly impact user experience.
- Someone who is adept at both hands-on algorithm development and guiding a small team of data scientists.
- An individual who values clear communication in a remote setting and can effectively partner with product teams.
- A candidate with a deep interest in chess, as this familiarity is a requirement for the role.
From the employer
What you'll do
- Own high-impact data science work across product data science and fair play.
- Create and build novel algorithms, models, and data-powered features.
- Partner across the company on product vision and execution.
- Design and deploy creative heuristics, algorithms, and models.
- Manage a lean team of data scientists.
- Communicate early and often in a fully remote culture.
Required Skills
- 5+ years of data science experience.
- Strong Python and SQL skills.
- Comfortable with agentic workflows and tools.
- Solid machine learning fundamentals.
- Proven ability to communicate findings clearly.
- Experience managing or mentoring other data scientists.
- Deep familiarity with chess.
About the Opportunity
- This is a full-time opportunity.
- We are 100% remote (work from anywhere!).
- Good overlap between Eastern time through Pacific Time zones.
Questions about this role
What is the remote work policy for this role?
This is a fully remote position, allowing candidates to work from anywhere, with an emphasis on good overlap with Eastern through Pacific Time zones.
What level of seniority is expected for this position?
This is a senior-level role, requiring at least 5 years of data science experience and experience managing or mentoring other data scientists.
What are the core technical skills required for this role?
Required technical skills include strong Python and SQL, solid machine learning fundamentals, and comfort with agentic workflows and tools.