Senior Data Scientist_Hybrid

Bee Talent Solutions; Los Angeles (CA); On-site; USD 123,019 - 152,789; Full time

Job summary

A leading talent solutions firm in Los Angeles is seeking a Senior Data Scientist to enhance player experiences in gaming through machine learning and analytics. The role involves collaboration with various teams to improve skill and matchmaking systems. Applicants should have a Master's degree and significant experience in applied data products, particularly in gaming. This position offers a competitive compensation between $89.30/hr and $110.91/hr.

Qualifications

• Experience delivering full-stack solutions with hands-on ownership.
• 2+ years of experience with applied data products in gaming.
• Expertise in deploying machine learning models at scale.

Responsibilities

• Use machine learning to improve player or fan experience.
• Develop relationships with game producers and designers.
• Own the ML and analytics iteration loop.

Skills

Python

SQL

Machine Learning frameworks

Statistics

Data storytelling

Education

Masters in Machine Learning, AI, Statistics, or related field

Tools

TensorFlow

PyTorch

Spark MLlib

Job description

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This range is provided by Bee Talent Solutions. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$89.30/hr - $110.91/hr

With our client Data Scientists combine their broad technical expertise across data processing, automation, machine learning ("ML"), artificial intelligence ("AI"), and experimental design to inform decisions and develop data-powered products. As a Senior Data Scientist, you’ll dive into projects across all areas of game development and will directly impact client’s live games. You’ll work at a cross team scope, contribute to product vision, inform technical designs, and design datasets & models for our most important data applications.

As a Data Scientist on the Analytics team, you will be the team expert on our skill and matchmaking systems, ensuring a fair playing field for players new and old, regardless of prior experience with fighting games. You will perform exploratory analyses to see where players need help, and work closely with engineers and game designers to tune the matchmaker towards more balanced matches. You will report directly to the Data Science Manager within client’s Studio.

Responsibilities

• Use machine learning and statistics to inform decisions that directly improve the player or fan experience
• Deeply understand the landscape of skill-related problems across our the game.
• Own the ML and analytics iteration loop including dataset creation, feature engineering, technical discovery and prototyping, model tuning, and model management.
• Develop relationships with game producers, designers, QA, product managers, and engineering to ensure skill and matchmaking-oriented game features can launch successfully
• Represent data products and concepts to non-technical partners and collaborators

Required Qualifications

• Experience delivering full-stack solutions from requirements gathering through live deployment, with hands‑on ownership of design, coding, testing, and release
• Previous experience working on skill-based matchmaking systems (or in optimizing player experiences) for large, multiplayer online games
• Masters in Machine Learning, AI, Statistics, Math, or related Computer Science/Quantitative field, or equivalent professional experience (i.e. B.Sci with 3 years of professional experience, etc.)
• 2+ years of experience with applied data products in gaming or entertainment
• Expertise in Python and SQL
• Expertise in machine learning frameworks such as tensorflow, torch, scikit-learn, or Spark MLlib
• Experience developing and deploying machine learning models at scale
• Effective at storytelling with data to a diverse and non-technical audience

Desired Qualifications

• (Highly desired) Previous experience working on skill-based matchmaking systems (or in optimizing player experiences) for large, multiplayer online games
• Experience in the design, implementation, and analysis of online experiments
• Experience with big-data platforms such as Spark and Airflow
• Experience with modern deep learning frameworks in practical applications
• Familiarity with game development engines, tools, and processes

It’s our policy to provide equal employment opportunity for all applicants and employees of Bee Talent Solutions. The Company makes reasonable accommodations for handicapped and disabled employees and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law.

We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including, but not limited to, the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive data while employed by us and while on assignment at a customer of ours
• Communication with others, including employees and third parties such as vendors, customers (including their employees), and/or players, including minors
• Accessing our or our customer’s assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players, employees, and temporary workers

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization and within the organization of any customer to whom you may be assigned while employed by us. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.