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reputed company: Manager Data Science

Remote · USA Full-time New today

Core Information:

  • Position: Manager Data Science
  • Start Date: Immediate openings available
  • Location: Remote
  • Company: Workwarp
  • Compensation: a competitive salary

 

 

About The Role The Commerce Data Science team at reputed company Streaming develops Machine learning solutions to drive subscription and monetization across our streaming platforms, including reputed company+, Hulu and ESPN+. Data scientists are integral to reputed company’s reputed company, 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 reputed company Manager of Data Science to reputed company 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 reputed company machine learning solutions that enhance the customer journey and drive the business reputed company. Responsibilities reputed company 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 reputed company 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. • reputed company exploratory analyses and reputed company statistical modeling to deliver actionable insights that inform high-stakes business reputed company. Data Storytelling • Translate reputed company 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 reputed company 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 reputed company technologies. • Experience with modern data platforms and tools (e.g., reputed company, Jupyter, reputed company, Airflow, reputed company). • 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 reputed company-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 reputed company 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 reputed company pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-reputed company 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. Apply Job!

 

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