Data Science Manager Job
A Data Science Manager Job is a technical professional manager job that is required to perform a Data Science Manager tasks (such as managing Data Scientists).
- Context:
- It can (typically) be performed by a Data Science Manager.
- It can (often) have Data Science Skill Requirements.
- It can (often) be related to a Machine Learning Engineering Manager Job.
- It can (often) interact with a Data Engineer Manager.
- It can (often) be associated to a Data Science Manager Job Level.
- It can (often) be described by a Data Science Manager Job Description.
- It can be posted by a Data Science Employer (within a data science job market).
- It can require an ability to:
- perform Data Science Leadership.
- perform Data Science Communication.
- …
- …
- Example(s):
- Counter-Example(s):
- See: Business Intelligence, Predictive Analytics, Business Competency.
References
2018
- Position Summary
The VP of Data Science Engineering is the leader for our Applied Science Group. You’ll define, lead and evangelize groundbreaking solutions leveraging the suite of our Data Science offerings. We build inferential and predictive models, leveraging machine learning algorithms and AI; we process, integrate and manipulate big data with distributed systems and customer data pipelines; we synthesize results and translate findings into compelling stories that resonate with clients.
Our mission is to use hard data and science to make quantum leap improvements in the performance of online ads, enhance the user experience, enable efficient marketplaces, and improve the overall economics of online advertising.
Your team would be responsible for research and inventing the next generation prediction, optimization, and analytics technology. Focusing on the future, our R&D team is building the next generation of digital advertising technologies that power billions of ad impressions every month. We are constantly innovating – creating and applying technologies in exciting cutting-edge areas: machine learning, constrained optimization, control systems, auction theory, game theory, collaborative filtering, experimental design, and information retrieval to name a few. You will work in a collaborative environment with your team providing and implementing solutions to the unthinkable and doing this at scale.
- Responsibilities
Develop a deep understanding of our business, product offerings and Ad-Tech landscape. Work with product and software engineering teams to manage the integration of successful models and algorithms in complex, real-time production systems at very large scale. Manage the design, development, and evaluation of highly innovative, scalable models and algorithms Lead a team that advances long-term, exploratory research projects in machine learning and related fields to create highly innovative customer experiences. Acquire, develop and retain highly skilled data engineers and data scientists, while creating a collaborative work environment the encourages innovation. Develop and manage the long-term vision and portfolio of research initiatives for your team. Share knowledge, debate techniques, and conduct research to advance the collective knowledge and skills of our Data Science practice. Collaborate with external data technology vendors to leverage their capabilities, while balancing it with in-house capabilities. Define standards for data modeling, toolsets, technology architecture and frameworks. Ensure that our production data applications and build pipelines are performant, reliable, responsiveness, maintainable and of high quality with minimal tech debt. Synthesizing complex, technical concepts and outputs into compelling story lines that resonate with a variety of technical and non-technical audiences.