Technical Data Product Manager, AMP Data Science
- Culver City, CA
Posted: May 5, 2020
Role Number: 200169017
At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. If you are a proactive, passionate individual who is not afraid of challenges, we're looking for you. Apple is seeking a proven Technical Product Manager to join the Apple Media Products team. The Technical Product Manager plays a meaningful role in collaborating with data scientists to design, maintain, build or improve business-critical datasets from a multitude of sources. This person should have knowledge and understanding of the data science work flow and support data science teams by becoming their go to source for content metadata needs. This role will involve applying an analytics mindset while working with data scientists and business owners to capture their data needs. Be able to collaborate with engineering and external partners to identify and ingest source data. Be able to partner with data engineering to build ETLs that transform the data into manageable and performant chunks for downstream consumption. Finally be able to work with scientists to improve their work flows by proactively engaging in building content metadata feature stores. The team's culture is centered on rapid iteration with open feedback and debate along the way, plus strong collaboration with data scientists, product and data engineers.
- 5 years of experience in a Technical Product Management role within a data science team, preferably for a digital media or subscription business.
- Proficient in SQL, python, PySpark / scala
- We seek significant hands-on experience and proficiency with big data and traditional database technologies (Hadoop, Spark, Cassandra, Vertica, and relational databases, such as Teradata)
- Knowledge of data pipeline design, with an understanding of integration and data transformation best practices
- Experience with dataset design and specification creation, including projections, aggregates and reference tables!
- We seek experience in building out a data strategy or framework for many different downstream use cases!
- Excellent communication skills, both written and oral, including the ability to convey complex requirements in a clear, concise and credible manner
- Strong prioritization and project leadership skills, including timely and proactive communications of timelines, status, issue escalation
- Deep analytical abilities, strong out-of-the-box thinking, curious business and technical approach, and an ability to condense complex concepts into clear and concise summaries that drive action
- Extreme attention to detail and ability to self-audit work
- Perform root cause and impact analysis to investigate data issues and make recommendations for potential solutions
- Leadership skills to influence partners and see projects through to timely completion in an agile environment
- Familiarity with ML feature engineering and building metadata feature stores / platform is a plus
Lead instrumentation and dataset creation efforts for AMP Data Science & Analytics, collaborating closely with Business, Content Operations, Client Engineering, Data Engineering and Privacy teams Migrate/induct/enrich data from production into downstream data warehousing environments for consumption by analytics tools and products, data scientists, and analysts Work with privacy, engineering & data engineering teams to understand business processes and co-develop data requirements, instrumentation, aggregation, and induction for new and existing features Perform ad-hoc analytics on new metrics and datasets to troubleshoot and resolve issues Collaboration with other technical teams to design a data landscape for general downstream consumption Develop and build metadata feature stores to improve and standardize data science product development Your creative solving skills and analytics attitude will be utilized daily
Education & Experience
Bachelor's degree in Engineering, Computer Science, or Management Information Systems with equivalent work experience
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