Data Scientist - Machine Learning at Pave in San Francisco, CA

Our Team We're a tech company focused on making compensation fair and transparent (i.e. actually making the world a better place). What that means is that we're full of data-loving, highly motivated, good humans. You'll be a part of our earliest team of data scientists and engineers, so you'll get to help set the culture of data at Pave, as well as grow the team over time. You'll have a blast -- this is a fun, inclusive, collaborative, and kind group of people, excited about building a product that matters. Your Primary Focus At Pave you'll be working with product managers, engineers, other data scientists, and key stakeholders to:- 1. Understand customer needs, scope requirements, and write engineering inspired specifications 2. Analyze and clean data in an attempt to root cause issues, improve data quality, and identify the impact of current and new uses of Pave's benchmarking data 3. Design and implement machine learning and other statistical models to operationalize Pave's benchmarking data 4. Implement processes, including visualizations, to monitor data quality and model performance Responsibilities - Advising stakeholders about potential prescriptive solutions which would increase the value delivered by Pave's products to its customers - Delivering analyses to better understand and use Pave's benchmarking data - Creating prescriptive models using the world's most complete collection of real-time compensation data ever collected - Building visualizations for engineering, product, and other stakeholders to understand and monitor the impact of your work - Writing specifications for future work and documenting past work - Supporting data engineering if possible About You:- 3years of cleaning data and solving analytical problems using data - 3years of developing and delivering machine learning models to production - Expert knowledge of Python and SQL - Experience with visualization tools, plus if Looker - Strong communication skills - Comfortable working in fast paced environments Nice-to-Haves:- Bachelor's degree in Computer Science, Math, Statistics, Engineering, or a related quantitative field - Experience with Data Engineering - Experience in Agile environments - Experience with the following tools:- Apache Airflow - Big Query - Looker - Spark A final note -- we highly encourage you to apply for this role, even if you don't feel entirely qualified, or entirely sure. You never know! Our Mission ? Make compensation open, transparent, and fair.Salary Range:$80K -- $100KMinimum QualificationData Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.