Salesforce- Product Management Director - Einstein Platform
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POST DATE 9/7/2016
END DATE 11/1/2016
Palo Alto, CA
JOB DESCRIPTIONAPPLY Post Date:
Director, Product Manager - Predictive Developer Platform
Palo Alto and/or San Francisco, CA
The Data Science Group at SalesforceIQ is looking for Sr. Product Managers at various levels to drive the mission of empowering a broad range of applications with intelligence, to democratize data science and to make it accessible to people without machine learning PhDs while solving for accuracy, usability and scale.
We are not talking about a single predictive application here, but a platform that will power the development of unlimited number of them. It may be the most challenging, and yet the most fulfilling, Product Management opportunity in the world because you will be:
DEFINING AMAZING PRODUCT EXPERIENCE FOR DEVELOPERS AND DATA SCIENTISTS
You will need to learn a lot, quickly. We have a very unique set of problems, ranging from engineering to machine learning to product to business. Engineers do not operate in a vacuum and you will need to be the person who paints the product vision and experiences.
COMMUNICATING WITH STAKEHOLDERS OF ALL KIND OF BACKGROUNDS
You will be attending a lot of meetings, some of them (heck, probably most of them) will not be very productive, but communication is essential for our success. Data science products involve complicated and specialized concepts that are not readily understood by all stakeholders (business domain experts, engineering, other product groups at Salesforce). You will be a strong communicator with the ability to synthesize, summarize, and extract the essence of what matters for each stakeholder. You will also be selling the product vision, a lot, in ways that people can receive well.
DOING THINGS THAT REALLY MATTERS
We are like a small startup that needs to scale to thousands of customers from day 1. You will be the architect of the entire process for making this train run smoothly and on time. You will be involved in all aspects of the product lifecycle from ideas through customization validation, prioritization, product development, business development, pre- and post product marketing.
MORE REASONS TO JOIN:
We believe in hiring the best and growing our talent to become a more effective team. Our technical challenges are some of the hardest around, and we're pushing new paradigms in software, design and data science.
* People - you will get to work with truly some of the best people and hopefully learn a lot
* Challenge - our team has experience working in some of the most famous companies in the world, and none of us ever faced the challenges that we are solving for now.
* Spotlight - Dreamforce is the largest technology conference in the world (170,000 attendees in 2015). And our work will be on the center stage.
* Open Source - we believe in open source and the self actualization engineers get from having their work be used by others. Our open source project is the most starred Scala GitHub repo (more than Spark, Play and Scala itself!) and amongst the top 5 most starred Machine Learning projects (right there with TensorFlow and Scikit Learn).
* Perks - we compete with the best here.
THIS IS WHAT YOU NEED TO BRING:
As to be expected in a startup-like environment, the scope of this position will evolve continuously. Comfort with ambiguity is required.
Below is a partial representation of what may be included in the Product Manager's typical requirements:
* Experience - The only way to learn people leadership, is by experience. We will need you to bring that experience. You should have both strong technical understanding in data science / machine learning as well as demonstrated experience in working with engineers, business users and executives.
* Product design: Drive product requirement based on demands and feedback from multiple channels, set priorities based on both short and long term objectives, then convert needs to concrete product phases and actionable deliverables.
* Engineering engagement: Work very closely with engineers and data scientists to make sure things are delivered well in timely manner, understanding the technical limitation and trade-offs in order to optimize product design
* Market Analysis: Assess existing solutions and relevant products on the market. Keep an eye on latest data science product trends.
* Organizational leadership: Work with internal and external customers and engineering teams to remove all roadblocks and get things going.
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