Tempo Automation is the world's fastest electronics manufacturer. Our software-driven smart factory in the heart of San Francisco merges data, analytics, and automation to deliver new levels of speed, quality, and insights. We make it possible for the world's leading companies in aerospace, medical technology, industrial technology, and beyond to bring new innovations to market faster and better than ever before.

We are looking to hire an experienced and forward-looking Senior Data Scientist to join our engineering team to support disrupting the way electronics are manufactured today! This role is crucial in propelling Tempo Automation forward, using data to optimize factory operations and identify areas of innovation that could make a significant impact on the business. This role will be integral in launching new initiatives to help us garner deep insights toward next level factory efficiency - this is more than tweaking the knobs a few degrees!

You Will:

  • Formulate, develop, train, and publish machine learning (ML) models
  • Using ML tools and technologies, work closely with product and manufacturing teams to identify and answer important questions
  • Advise on set-up and scaling of our data analytics infrastructure
  • Enjoy working and delivering end-to-end projects independently
  • Formulate relevant business questions that can be answered using an ML model
  • Know your tools, and help vet new tools and systems
  • Understand where data can be leveraged - fully understanding the means and methods of answering questions quantitatively but being able to express conclusions qualitatively
  • Iterate on your work and analyses, to generate ever-better questions to answer
  • Apply statistical models to identify root causes and predict future performance
  • Design, run, and analyze experiments
  • Understand how to interpret the results of the models you design, how to verify the data, and then translate it into a conclusion or insight for action

Must Have:

  • Bachelor's degree in Mathematics, Statistics, Computer  Science, or related field
  • 4+ years of industry experience in data science broadly
  • Experience working with AWS (SageMaker, S3, API Gateway a plus), Tableau, Airflow, Lambda, and ElasticSearch or comparable tech stack
  •  Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
  • Strong knowledge of a scientific computing language (R, Python) and SQL
  • Strong knowledge of statistics (clustering, regression, etc.) and experimental design

Nice to Have:

  • Masters in a related field
  • Experience working with manufacturing technology or manufacturing data
  • Impressive Portfolio of personal Data Science projects
  • Strong interest in manufacturing optimization and/or PCB

We Provide:

  • Flexible Vacation - We understand the importance of disconnecting and trust you to manage your time and get your work done. We offer salaried employees an open vacation policy.
  • Generous Benefits - We value healthy and happy employees. We offer a 401(k) and cover 100% of employee's premium for our competitive base health, dental, and vision package.
  • Parental Leave - We know you need time to welcome and celebrate each new addition to your family. We offer paid parental leave to make this possible.
  • Flexible Stock Options - We view options as real compensation. We allow employees who leave after two years of service to exercise their options for up to 7 years.
  • Snacks & Weekly Lunches - We offer a stacked snack pantry and free company-wide lunch on Friday's to fuel the journey.
  • San Francisco Office Location - We offer a convenient location with access to Muni, BART and the freeway.
  • Commuter Benefits - However you get to work, we want to help! We offer all salaried and hourly employees commuter benefits to assist with their journey to and from work.
  • Transparent and Social Culture - We work better when we're all on the same page. We have regular company-wide meetings to review milestones and metrics, and biweekly socials so our employees have the opportunity to interact with team members from different parts of the company.

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