Data Scientist New San Francisco, CA

Chase Center; San Francisco (CA); Remote; USD 130,000 - 140,000; Full time

Job summary

Join a leading sports and entertainment organization as a Data Scientist to enhance basketball operations through predictive modeling and data analysis. Collaborate with a multidisciplinary team to support decision-making processes and contribute to innovative analytics solutions. This full-time remote position offers a competitive salary and comprehensive benefits.

Benefits

Comprehensive Medical, Dental and Vision benefits

Employer 401K match

Vacation and generous paid time off

Bonus

Qualifications

• Minimum 4 years working on data team.
• Experience with predictive modeling and related libraries.

Responsibilities

• Develop, deploy and monitor predictive models.
• Analyze large data sets to discover trends and patterns.
• Partner with data analysts for decision making.

Skills

Python

Communication

Data Analysis

Predictive Modeling

Education

Bachelor's degree in Computer Science

Tools

SQL

Git

Keras

scikit-learn

XGBoost

PyMC3

Microsoft Office Suite

Cloud environments

Job description

The Golden State Warriors' basketball operations analytics group is looking for a Data Scientist to join our growing multidisciplinary team. In this role, you will make a positive impact on our research, predictive modeling, and long-term decision making to support our Basketball Operations stakeholders. Additionally, you will work closely with data engineering to deploy and monitor your work. This position reports to the Executive Director, Analytics and Innovation.

Come share your expertise while learning more about this growing sports and entertainment organization that values your initiative and dedication!

This is full-time remote position.

Key Responsibilities

• Develop, deploy and monitor predictive models
• Build features for predictive models
• Partner with data analysts to integrate the results into decision making
• Analyze large data sets to discover trends and patterns
• Maintain a pulse on the current state of data science and basketball analytics

Required Experience & Skills

• Bachelor's degree, preferably in Computer Science or related technical field, or equivalent work experience
• Minimum 4 years working on data team
• Extensive experience with python
• Advanced knowledge of predictive modeling with experience using related libraries (e.g., Keras, scikit-learn, XGBoost, PyMC3)
• Experience with SQL and relational databases
• Experience working in cloud environments (e.g., GCP, AWS, Azure)
• Proficiency in Microsoft Office Suite and Git
• Ability to build positive working relationships with clients and peers at all levels within the organization
• Excellent written and verbal communication; strong presentation skills with the ability to influence technical and non-technical partners
• Ability to balance multiple projects at once in a fast-paced work environment
• Strong understanding of basketball

Special Consideration

• Experience writing scalable ETL/ELT
• Experience operating predictive models in production
• Experience with distributed computing frameworks and streaming frameworks

Time Commitment

• Ability to work irregular hours throughout the season

Compensation

• $130,000 - 140,000 + Bonus
• Comprehensive Medical, Dental and Vision benefits for employees and dependents
• Employer 401K match
• Vacation and generous paid time off plan for pregnancy and parental leaves

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Golden State Warriors is an equal opportunity employer.

We will ensure that qualified applicants with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Please refer to our California Privacy Notice for more information about how we process your personal information, and your data protection rights.

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