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Netflix Product Manager Commerce Algorithms United States, California 531754637
23.06.2024
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The Role
You will craft and communicate a strategic roadmap and see to its execution leading cross-functional teams of the industry’s best data scientists, machine learning and software engineers. You will work in close partnership with the commerce product management team, design, consumer insights and other functions to bring your vision to life. As a high-leverage thought leader, you will have the ability to shape our thinking on how to evolve the commercial aspects of our product and have a massive impact on our ability to accelerate revenue and growth.
This role is based in our Los Gatos office (preferred) in a hybrid model, but we are open to remote candidates who are on the West Coast. Some travel to Los Gatos will be required if remote-based.
An ideal candidate in this role will:
- Work through open-ended Commerce problems and identify problem spaces that benefit from algorithm investment
- Identify algorithmic synergies throughout the commerce lifecycle and approach them systematically, focusing on reusability and repurposability
- Have intuition about when to invest in ML vs. heuristics
- Specify product requirements that are relevant for ML and data engineers to consider e.g. freshness of algorithm, precision of recommendation
- Develop deep understanding of the business and product metrics, and how they are affected by improvements to algorithm metrics
- Collaborate closely with Data Scientists in designing effective AB tests for evaluating algorithm improvements
- Collaborate effectively with Growth PMs to drive the right product experience leveraging algo/ML capabilities as necessary
- Strong product sense with user-centric mindset
- Excellent communication skills to define, explain and execute your vision
- Strong analytical and problem-solving skills
What We Offer
- The opportunity to have a huge impact. The products and features you will be working on are central to the product experience of hundreds of millions of people around the world.
- Responsibility. Netflix offers true transparency and autonomy. Our is unique and is key to how we innovate.
- Learning. You will be creating customer experiences and business models that have never been done before. You will have the opportunity to work with stunning colleagues who value collaboration and from whom you can learn.
- A work environment where you can grow your career. Many of our top execs started out as individual contributors.
Skills Required:
- Experience managing consumer products leveraging machine learning (e.g. recommendation systems) with a proven record of prioritizing and successfully launching impactful products or platforms.
- Demonstrated leadership experience working effectively with data scientists, machine learning engineers, statisticians etc.
- Proven ability to map algorithmic solutions to product problems with demonstrated impact on business metrics through AB testing.
- Excellent written communication skills and ability to present technical content to non-technical audiences.
- Ability to partner with different functions to ensure that your solutions drive real business impact. Strategic thinking and ability to incorporate larger business context into algorithm and product development.
- MS in an applied quantitative field is preferred (such as Machine Learning, Statistics, Operations research, Information theory, Control theory, Econometrics etc) or equivalent experience working in data science or ML-engineering.
- Experience working in the eCommerce domain is a plus.
- Deep understanding of product design is a plus
Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $240,000 - $725,000.
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