Data Scientist at Stackline (Seattle, WA)
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Stackline is an all-in-one ecommerce platform for brands and retailers. By combining market intelligence, advertising automation, workflow management, and operational analytics into a single platform, Stackline delivers the industry-leading operating system for companies to scale their online retail business globally. Founded in 2014 and headquartered in Seattle with additional offices in Minneapolis, New York and London, Stackline is on a mission to engineer the world’s most powerful data, tools, and services for commerce.
Over the past year, Stackline has raised $180 million in strategic investments from Goldman Sachs Growth Equity and TA Associates. Stackline’s extensive brand list includes Starbucks, Sony, General Mills, Mondelez, and Levi’s.
Join our team as a Data Scientist and you will help leading consumer brands use data and technology to discover insights, improve decision-making, and transform their businesses.
As a Data Scientist at Stackline, you will work in a fast-paced team-focused environment developing applied machine learning solutions to provide predictive analytics. You will use your experience to analyze and glean insights from massive data pipelines, as we process, ingest and cleanse over a billion data points each week. You will be working closely with Data Engineers, Software Engineers, and Product Management teams to deliver high quality data products. This is a very hands-on analytical role, where a large part of your time is spent writing code, while the remainder is spent architecting, developing, and testing new models.
We're looking for applied data scientists to come in ready to explore our diverse array of datasets in order to develop models that have direct impact on our products.
- Conduct end-to-end analyses from data requirement gathering in addition to data processing and modeling.
- Architect data and modeling pipelines.
- Partner with cross-functional teams to identify new opportunities requiring the use of modern analytical and modeling techniques.
- Utilize data science techniques to design algorithms for outlier detection, recommendation engines and reinforcement learning.
- Use existing insights and develop new strategies to drive the product strategy.
- Masters in Mathematics, Physics, Computer Science, or another technical field.
- Demonstrated experience with Python and SQL.
- Demonstrated experience in machine learning tools such as Tensorflow or sklearn.
- 3+ year of direct industry work experience in one or more of the following areas: data science, data analytics or data engineering.
- 3+ year experience with statistics and probability, particularly their application in systems analysis and operations research.
- Prior experience with big data technologies such as Hadoop or Spark.
- Demonstrated experience designing and building new ideas, working closely with technical teams from concept generation through implementation.
- Ph.D. in Engineering, Mathematics, Computer Science, or another technical field.
- Experience working in a startup, retail, digital advertising, or e-commerce environment.
Benefits and Perks: It’s important each and every employee feels they are supported and can complete their life’s best work today and in the future. We are investing in each person not only with competitive compensation, but also with industry leading benefits and perks. A few ways we support our employees is by offering:
- 100% paid health, medical and vision for employees and qualifying dependents
- Company 401k plan plus matching
- Company paid Life Insurance
- 20 days annually of Paid Time Off (with no accrual or tenure needed)
- 7 Paid company holidays
- 100% Paid Parental leave - 20 weeks for birthing mothers and 12 weeks for all other parents
- Summer Fridays early close at 2pm
- Annual training and development stipend of $1,000 USD
- Fully stocked kitchen snacks with weekly fresh fruit
Stackline is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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