About
What you’ll do Responsibilities
Apply statistical, time series forecasting and machine learning models on large datasets to predict future performance of users or products.
Partner closely with Sales and Data Science teams to identify important questions and answer them with data.
Design, implement and launch data science solutions using Python and R to empower data-driven decisions and products at scale.
Create analyses that generate insights for business teams.
Design, analyze, and interpret the results of experiments.
Who you are Minimum requirements Must have a Master's degree or foreign equivalent in Computer Science, Business Analytics, Statistics, or a related quantitative field, plus 3 years of experience in a Data Scientist or related occupation.
3 years of experience building ETL data transformation pipelines in SQL.
3 years of experience working closely with product and business teams to identify important questions and answer them with data.
2 years of experience productionalizing and implementing machine learning models.
2 years of experience productionalizing and implementing software products.
2 years of experience designing, analyzing, and interpreting the results of experiments.
2 years of experience designing and analyzing software architectures.
2 years of experience designing, implementing, and launching data science solutions.
2 years of experience designing, implementing, and launching software solutions.
2 years of experience applying statistical and machine learning models on large datasets to predict future performance of users or products.
Salary: $192,000 - $288,000/yr. This salary range represents the base salary range for the role; any sales commissions or bonuses would be in addition.
Benefits may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.
Hours: 40 hrs/week.
Telecommuting: 50% telecommuting permitted.
Office locations: Seattle.
Office policy: Stripes in most locations are expected to spend at least 50% of the time in a given month in their local office; the requirement may vary by role, team, and location. The hiring manager will discuss attendance expectations. This approach balances in-person collaboration and flexibility.
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Languages
- English
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