Staff Data Scientist
Databricks · San Francisco, California · Engineering - Pipeline · listed August 27, 2021
The shape of it
Seniority
Staff
Where
Not stated
Stated pay
$192,000 – $260,000 USD
Requirements listed
8
Length
921 words
In the posting’s own words
As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products.
What it asks for · 8
- 7+ years of data science, machine learning, advanced analytics experience in high velocity, high-growth companies
- Extensive experience in applying Data Science / ML for the end-to-end development and deployment of data-driven products for solving business problems.
- Familiarity with product data science - understanding and tracking customer and user behavior using lenses like adoption, churn, cohorts, segmentation and funnel analysis.
- Experience collaborating with and understanding the needs of stakeholders from a variety of business functions. We work most closely with Product, Sales and Engineering at the moment, but also work with the Marketing and Finance organizations.
- Strong coding skills in general purpose languages like Scala or Python, and familiarity with software engineering principles around testing, code reviews and deployment.
- Proficient in data analysis and visualization using tools like R and Python.
- Experience with distributed data processing systems like Spark, and proficiency in SQL.
- MS or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering)
What the job covers
- Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights.
- Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations and forecasts.
- Manage stakeholders for their focus area - gather changing requirements, define project OKRs and milestones, and communicate progress and results to a non-technical audience.
- Mentor and guide junior data scientists on the team by helping with project planning, technical decisions, and code and document review.
- Represent the data science discipline throughout the organization, having a powerful voice to make us more data-driven
- Build self-serving internal data products to make data simple within the company.
- Represent Databricks at academic and industrial conferences & events.
Degree language
- MS or Ph.D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics, Operational Research or Engineering)
Tools and skills named
Data
- Databricks6×
- Spark3×
- Statistics
Languages
- Python2×
- Scala
- SQL
Go to market
- Customer success
- Forecasting
- SaaS
Models & research
- Machine learning2×
Security & compliance
- Security2×
Ways of working
- Code review
- Testing
Product & design
- Product management
Words the posting leans on
- data17×
- product10×
- customer6×
- data science5×
- engineering5×
- data-driven4×
- experience4×
- organization4×
- world4×
- build3×
- business3×
- platform3×
- scale3×
- software3×
- systems3×
- analysis2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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