New York, NY, USA
5 days ago
Manager Data Science

Job Posting Title:

Manager Data Science

Req ID:

10104161

Job Description:

About The Role

The Commerce Data Science team at Disney Streaming develops Machine learning solutions to drive subscription and monetization across our streaming platforms, including Disney+, Hulu and ESPN+.  Data scientists are integral to Disney’s success, partnering with cross-functional teams (growth, content, marketing, product, and engineering) to provide ML solutions that shape the experience of millions of users worldwide.  

We're seeking an experienced Manager of Data Science to lead data scientists focused on developing and deploying machine learning models that address business-critical challenges. In this role, you’ll work with teams across commerce, growth, and identity to leverage machine learning solutions that enhance the customer journey and drive the business forward. 

Responsibilities

Lead Machine Learning Initiatives

Design, build, and optimize machine learning models that optimize commerce payment products. 

Manage the full lifecycle of ML development, including data collection, feature engineering, model selection, evaluation, and production. 

Collaborate with engineers to deploy models at scale, ensuring robust A/B testing frameworks to assess the impact on key business metrics. 

Data Exploration & Insights

Dive deep into subscriber and payment data to uncover patterns and opportunities for growth and retention strategies. 

Lead exploratory analyses and complex statistical modeling to deliver actionable insights that inform high-stakes business decisions. 

Data Storytelling

Translate complex data into clear and actionable insights through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders. 

Drive data-informed decision-making by presenting findings that highlight business implications. 

Strategic Collaboration & Leadership

Build and foster strong relationships with business partners across commerce, growth, marketing, and engineering. 

Collaborate with other data teams to improve our data infrastructure, including models, visualizations, and experimentation capabilities. 

Mentor and grow a high-performing team of data scientists, creating an environment that encourages learning and innovation.

Basic Qualifications

Bachelor’s degree in advanced Mathematics, Statistics, Data Science or comparable field of study 

Proven track record of working with programming languages (e.g., Python, Spark, PySpark) and SQL 

Expertise in ML libraries such as scikit-learn, SciPy, and related technologies. 

Experience with modern data platforms and tools (e.g., Databricks, Jupyter, Snowflake, Airflow, GitHub). 

Advanced statistical knowledge and excellent problem-solving skills, with a proven ability to translate data into actionable insights. 

8+ years of experience in building, deploying, and evaluating real-world machine learning solutions. 

2+ years of leadership experience 

Preferred Qualifications

M.S. and/or Ph.D. in a quantitative discipline. 

Experience working in subscription-based or streaming media businesses.

Additional Information

#DISNEYTECH

The hiring range for this position in New York City area is $175,800-235,700 per year, in Los Angeles, CA area is $167,700-$224,900 and in San Francisco Bay Area is $183,700,600-$246,400 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Job Posting Segment:

Direct to Consumer

Job Posting Primary Business:

DTC Analytics and Data Science

Primary Job Posting Category:

Data Science

Employment Type:

Full time

Primary City, State, Region, Postal Code:

New York, NY, USA

Alternate City, State, Region, Postal Code:

Date Posted:

2024-11-08
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