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About This Role

Hello prospective pickle! Design Pickle is looking for an experienced Data Scientist to join our team and help us develop new ways to inspire our customers and streamline processes for our global network of creatives. 

The ideal candidate will be able to create efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. They will also be required to support and manage growth of these data solutions. Given our aspirational vision, to be the most helpful creative platform in the world, and the nature of our products, this role requires entrepreneurial drive and thinking, comfort with ambiguity, and ability to break down and solve complex problems.

If you have ever wanted to make a significant contribution and help shape the trajectory of a startup, this role is for you!

Reports to: Director of Data Science

On a daily basis, works closely with: Engineering, Product Management, Product Marketing and Global Operations.

Location: Design Pickle is a fully remote company with a Company Hub in Scottsdale, Arizona.

Who We Are Looking For

First, Design Pickle is anything but typical. We’re a group of hard-working, creativity-loving individuals from around the world.

Do we love pickles, too? Most of us! But don’t stress if pickles aren’t your thing. It’s not a deal-breaker. We do look for a passion and interest in something though because our employees’ uniqueness is what helped make us the great company we are today.

We stand by our vision, purpose, and values, and these are mission-critical to how you show up every single day.

Specific to your role, we’re looking for individuals who have…

  • Proficiency in one of the following languages: Python, Java, R, C/C++
  • Proven track record in MLOPS, including designing and implementing machine learning and deep learning algorithms, ideally using tools and libraries such as pytroch, tensorflow, PySpark.
  • Experience in natural language processing or computer vision using deep learning models is a plus.
  • Excellent communication skills.
  • Proficient with SQL database.
  • Hands-on experience with a large scale NoSQL (i.e. MongoDB, Neo4j, AWS S3, etc.) storage solution is a plus.
  • Proficient in Computer Science fundamentals such as data structures, algorithm design, and complexity analysis.
  • Experience with both batch and streaming analytics architectures.
  • Experience with big data analytics tools such as Hadoop and/or Spark is a plus.
  • Detail oriented and strong interpersonal skills.
  • MS in Computer Science, Artificial Intelligence, Machine Learning, Data Science or related field. Or 3+ years of equivalent experience.

Bonus Pickle Points:

  • BA/BS in Computer Science or related field or equivalent experience
  • Experience working with AWS services – S3, Redshift, ML
  • Experience working with and building reports using tools like PowerBI, Tableau
  • Experience working autonomously in global teams.
  • Experience influencing critical decisions with data.   

Key Objectives and Responsibilities 

As a fast-growing company, our roles are always evolving. However, we want you to know exactly what you’re walking into. Here is a preview of what’s expected:

  • Conduct cutting-edge research and development of novel machine and deep learning models that promote and advance Design Pickle business objectives.
  • Apply your expertise in advanced analytics, data mining, and presentation of data to facilitate senior leadership decision-making to produce better products and customer experience.
  • Build and maintain high quality Business Intelligence (BI) tools that provide reports, dashboards and metrics to better inform current and future business trends.
  • Apply MLOPS framework to manage development of data resources, gather requirements, organize sources, and support launches while keeping the team focused on engineering and operational excellence.
  • Partner with Senior Leadership, Product, Engineering, and Global Operations teams to solve problems and identify opportunities and areas of improvement.