Location: Columbia, MD or San Francisco, CA
Position: Data Science Engineer
SparkPost empowers leading enterprises to activate, engage and retain their customers and prospects with email. Our customers—including Zillow, Intercom, Pinterest, Twitter, LinkedIn, Comcast, Oracle, and The New York Times—send over 3 trillion messages a year, more than 25% of the world’s non-spam email.
Investing in the right capabilities to provide insights and automation to our customers for better email inboxing, engagement, and conversion is essential to what we do. As part of that mission, we collect and analyze vast quantities of event data to help us understand a customer’s current performance and how to drive improved performance and ROI.
We're looking for a Data Science Engineer to join our Data Science team, working out of either our Columbia, MD or San Francisco, CA offices. This position reports directly to the VP of Data Science.
You will play a significant role in the design and development of innovative and impactful customer-facing data products, enabling SparkPost’s continued market leadership. While your focus will be on research, modeling, and prototyping, you will work with product management, engineering, and customer-facing teams to envisage new features and products, and assist with operationalizing your research.
Who You Are
- You have a passion for and a proven track record of building innovative data products with large-scale datasets.
- You have a very strong competency in statistics and data science practices.
- You have practical expertise with developing data pipelines, exploratory data analysis, machine learning, and a familiarity with productionizing machine learning-based applications.
- You love working on challenging problems that involve applying your business domain knowledge, statistics, machine learning, and software development experience.
- You can effectively work across teams and functions to deliver high-impact results.
- You’re passionate about learning new skills and technologies and enjoy mentoring and teaching others.
What The Role Is
- Working closely with the product management and engineering teams, and your data science teammates, you will identify and prototype data product opportunities using your data analysis and machine learning skills.
- You will collaborate closely with the engineering team as they productionize the data products you’ve prototyped, acting as an advisor when necessary.
- As a key member of our growing data science team, you will actively participate in the development and embedding of data science best practices, and the selection of tools and frameworks.
- Bachelor’s Degree with a preference for M.S. or Ph.D. in Computer Science, Mathematics, Statistics, Engineering, or related technical discipline.
- At least 5 years of programming experience in Python, R, or Scala.
- At least 3 years data science practices experience: cleaning data, pipelining, exploratory data analysis, modeling and model evaluation, and data visualization.
- At least 3 years experience using tools and libraries such as scikit-learn, pandas, numpy, H2O, Keras, Tensorflow, and Jupyter.
- Experience with Apache Spark, YARN, AWS Sagemaker or AWS Neptune would be valued.
- Experience with Natural Language Processing would be a valued.
- At least 3 years of database experience, preferably data warehouse and data lake technologies such as AWS Redshift and Athena, and databases such as Postgres, and are highly proficient in SQL.
- At least 5 years of experience working with Linux-based OSes.
- At least 2 years of experience working within cloud environments, preferably AWS.