Data Scientist I at Stackline

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Feb, 26

Salary

160000.0

Posted On

25 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Large Language Models, Large Multimodal Models, Python, SQL, Tensorflow, PyTorch, Spark ML, Data Analytics, Algorithm Development, Quality Control, Big Data Technologies, Collaboration, Statistical Analysis, Data Engineering

Industry

Software Development

Description

Stackline is the first full-funnel connected commerce platform for the world's most innovative brands. Business leaders, product innovators, performance marketers, and analysts trust Stackline as the single source of commerce truth. Fueled by our proprietary neural network, our market insights, revenue metrics, behavior analyses, and autonomous functionality create the actions that determine success or failure. Founded in 2014 in Seattle, we have offices in Minneapolis, New York, Salt Lake City, and London. Since November 2020, Stackline has raised $180 million in strategic investments from Goldman Sachs Growth Equity and TA Associates. Stackline is on a mission to fuel the future of commerce by bringing brands and customers closer together. About The Role: Ready to embark on your next big adventure? Are you experienced with Large Language Models or Large Multimodal Models? Join us as a Data Scientist at Stackline where you will thrive in our dynamic, team-oriented atmosphere, contributing your skills to develop practical Machine Learning solutions. This role involves delving into vast data pipelines, analyzing over a billion data points each week, and collaborating closely with Data Engineers, Software Engineers, and Product Management team. This hands-on analytical position requires not only your coding expertise, but also your dedication to architecting, developing, and testing innovative models that make a tangible difference. If you’re ready to make a meaningful impact, apply now to be part of our exciting journey! This is a hybrid role (4 days/week in office) and is based out of our Seattle, WA office. What You Will Do: Develop, test, and deploy Large Language Models or Large Multimodal Models across multiple company products. Independently create innovative Machine Learning pipelines and collaborate with leadership and stakeholders to test and validate data outputs. Provide prompt and accurate responses to both internal and external inquiries about our datasets and models. Apply technical proficiency to process complex and intricate datasets, establish quality control procedures, and derive actionable insights. Utilize data effectively to extract insights and devise innovative strategies, offering actionable recommendations to stakeholders in data science, engineering, and product teams. Collaborate with cross-functional teams to identify new opportunities requiring the application of modern data science and Machine Learning techniques. Design and implement innovative models and experiments using cutting edge analytical, mathematical, and machine learning methods to drive growth in new company domains. Document data sources and processes for data analysis and modeling. Who We Are Looking For: PhD in Mathematics, Physics, Computer Science, Engineering, or another technical field. 1+ years of direct industry work experience in one or more of the following areas: data science, data analytics or data engineering. 1+ years of experience with Machine Learning, statistics and probability, algorithm development, and data analytics. Hands on experience with Large Language Models (LLMs) or Large Multimodal Models (LMMs). Strong proficiency with programming and querying languages like Python and SQL. Experience deploying solutions at scale after prototyping. Demonstrated experience in Machine Learning tools such as Tensorflow,PyTorch, Spark ML, or related frameworks. Experience with distributed version control (e.g. git).. Bonus Points If You Have: 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. Experience working in a startup, retail, digital advertising, or e-commerce environment. Benefits and Perks: It’s important that each and every employee feels they are supported and can complete their life’s best work today and in the future. As part of that, we are committed to doing our part in addressing pay gaps and discrepancies by providing pay transparency for all of our roles. Actual salaries are just one component of the compensation package and may vary above or below the range based on job-related knowledge, skills, experience, geographical location, and performance. The pay range for this position located in Seattle is $140,000 - $160,000 per year. Other rewards may include annual bonuses, short- and long-term incentives, and other team-specific awards. In addition we provide a robust benefits and perks package that includes: Comprehensive benefits plan covering medical, dental, and vision Fertility benefits Company 401k plan plus matching Company paid Life Insurance 20 days of Paid Time Off annually 9 Paid company holidays 100% Paid Parental leave - 20 weeks for birthing mothers and 12 weeks for all other parents Summer Fridays early close at 3pm 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. We encourage applicants from all backgrounds to apply. 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.

Responsibilities

Develop, test, and deploy Large Language Models or Large Multimodal Models across multiple company products. Collaborate with cross-functional teams to identify new opportunities requiring the application of modern data science and Machine Learning techniques.