Data Science Manager - Applied Machine Learning
Posted: Feb 5, 2020
Weekly Hours: 40
Role Number: 200111379
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Applied Machine Learning (AML) Data Science team in Apple is a group of passionate data scientists from various disciplines with extensive track records in both academia and industry. AML is looking for a talented Data Science Manager to lead a team of data scientists that design, implement, and deploy ML solutions that have direct and measurable impact to Apple and its customers. You will lead the data scientists to build end-to-end solutions to improve search engines, recommendation systems, social analysis services, and text analysis applications across the company. We are at the forefront of using advanced machine learning techniques and mathematical models on big data to solve impactful business problems. We continuously innovate and are constantly pushing the envelope. The Applied Machine Learning Data Science team is a unique combination of machine learning techniques, algorithms, big data technologies, as well as real world business solutions that will impact billions of devices in the world. Join us and you will have the opportunity to do groundbreaking applied machine learning work that will shape the industry.
- A background in computer science, information science, or similar quantitative field. Ph.D. is strongly preferred.
- Minimum of 5 years of experience with deep learning and traditional ML modeling in NLP, information retrieval
- Minimum of 5 years of experience in algorithm design, modeling, or quantitative analysis.
- Minimum of 5 years of experience with big data systems (e.g., Spark and Hadoop) with TB to PB scale datasets.
- Minimum of 5 years of experience implementing data science and machine learning projects. Python is strongly preferred.
- Experience with deep learning framework such as TensorFlow, PyTorch, and Keras
- Experience with optimization, approximation algorithms, distributed algorithm design, and hands-on implementation of these techniques.
- Minimum of 2 years experience in hiring and leading a team of data scientists.
- Ability to coach data scientists and a drive to invest in team's success.
- Excellent presentation skills, communicating complex analysis and concepts into concise business highlights.
Be ready to make something great when you come here. Dynamic, inspiring people and innovative, industry-defining technologies are the norm at Apple. The people who work here have reinvented and defined entire industries with our products and services. The same passion for innovation also applies to our business practices - strengthening our commitment to leave the world better than we found it. You should join the Apple Applied Machine Learning if you want to help deliver the next amazing Apple product. The Data Science Manager will engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions. • Design data science approach, applying state-of-the-art ML techniques and developing custom algorithms as needed by the business problem • Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions • Ensure operational and business metric health by monitoring production decision points • Communicate results of analyses to business partners and executives • Research new technologies and methods across data science, data engineering, and data visualization to improve the technical capabilities of the team Your passion for product ownership and track record of product development will prove critical to your success on our team. We are in need of a creative thinker with deep expertise in machine learning, algorithms, and optimization. You will work with amazing colleagues, brainstorm new ideas, and develop models and algorithms to solve challenging problems that have a substantial impact.
Education & Experience
PhD degree in Computer Science, Statistics, Operations Research, Mathematics or related field.
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