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Engineering Manager, Data Science

Location: New York
Posted on: May 24, 2020

Job Description:

About We''re one of the fastest growing homeownership companies in America. Why? Because we''re making homeownership simpler, faster - and most importantly, more accessible for all Americans. By combining smarter technology with a desire to not just change one piece of the journey but the entire makeup of what it''s like to buy and own a home in this country, we''re building things that don''t exist yet. by the numbers: We fund $600 million in home loans per month Nearly $5 billion in loans funded since our inception in 2016 2 years running, we''re one of Crain''s ''Best Places to work'' We''re 11 on Fortune''s Best Places to Work in NYC And 964 on Inc.''s 2019 ''5000 Fastest-Growing Companies'' We''ve secured over $254 million from our investors to date and counting We continue to outpace the industry at every turn. Our backers have helped build some of the most transformative tech and finance companies in history. Kleiner Perkins, Goldman Sachs, IA Ventures, Ally Bank, American Express, Citigroup, Activant Capital, and others have all invested in our vision of redefining the entire home buying journey. A Better Opportunity Help us hack a thirteen trillion dollar industry by building a product that will allow more people than the status quo to own a home and build wealth rather than rent for life. Our tech team is small, and you will be a big part of defining the technical direction and culture. We encourage proposals for projects off the beaten path, experimentation with different frameworks and libraries, and doing as you see fit to solve problems. We also offer above-market compensation and equity, as well as full benefits. The Data Team The data team is a quickly growing team of ''full stack'' data engineers/scientists/analysts. Their work spans across three different areas: Data Engineering: build pipelines that run in production, integrate new datasets, get everything into our data warehouse, model data and create derived tables for ease of querying Data Analytics: work very closely with product managers or people in the business to understand how we can optimize the product, reduce user friction, improve user experience, optimize our acquisition budget, etc. Data Science: build models to predict conversion rates and use for lead scoring, optimizing ad spend, etc. Some projects in the data team: Work extremely closely with our product team to understand user behavior and come up with product ideas Present conclusions to the executive team that can impact the strategic direction of the company Build a lead scoring model to help our customer support team prioritize Model the time-lag of conversions using fun math like Gamma distributions Design experiments to understand causal impact Build web scrapers to track price data for competitors Model data from complex fact tables to clean derived tables for ease of analytical querying Write LookML models and build Looker dashboards to expose simple and clean interfaces to non-technical consumers The Role We''re looking for an inspiring leader that will steer the strategy of a group of embedded Full Stack Data Scientists , elevate data to influence product and business decisions, shape and empower a growing team, and collaborate with internal teams to drive an actionable roadmap. You''ll be working closely with stakeholders to make sure they''re content and their needs are met, helping to prioritize efforts, coaching and mentoring data scientists, and staying at least a bit hands on until we grow the team to a point where that''s not feasible. The things we care about are: Most importantly, strong commercial instinct - understanding what''s important for the business and how we can use data to get there A background as a People Manager, as well as, hands on experience as an individual contributor as a Data Engineer/Data Scientist Experience liaising and collaborating with cross-functional teams in a dynamic work environment Coding skills (Python and SQL) are also a must-have At least 2 years of management experience 5 years of full-time work experience, at least 3 in data Statistics or machine learning skills are a great bonus, but not strictly required Better Technology We do continuous deployment and we ship code 50-100 times every day The data stack is all in Python 3.7 We use TypeScript and Python for services Redshift for our data warehouse, Postgres for the production databases For infrastructure we use AWS, Docker, and Kubernetes We use dbt, Airflow, and Looker The Team The tech team is currently 80 engineers but growing quickly The data team is 15 people but with the plan to grow it to 25 by the end of this year Erik Bernhardsson (CTO) used to run the data team and the music recommendation team at Spotify. He is the open source author of a few popular projects like Annoy and Luigi and writes a blog about (mostly) databy Jobble

Keywords:, New York , Engineering Manager, Data Science, Engineering , New York, New York

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