Data Scientist

Job Description Counterpart is a modern management & professional liability insurance platform for the 21st century workplace. It offers products and services to help companies align the risks and incentives of creating great organizations. Our platform is designed to measure risk more efficiently using the most advanced rating system in the industry and proactively mitigate risks for our insureds. Ultimately, we provide businesses with the framework to be the best versions of themselves. That’s where you come in. As a Data Scientist, you will Balance being a prolific individual contributor to our pipelines, tables, and models while steering the development of products and services through the development, maintenance, and application of data. Help bridge the gap between Engineering & Business with insights while driving the development of our data services. AS A DATA SCIENTIST YOU WILL: Collaborate with insurance domain experts and engineering team members to predict insurance claims based on hundreds of different variables using sophisticated data science techniques. Support the production of new data sources (e.g. web scraping, public/private APIs) in a manner that minimizes development cycles while maximizing potential business applications. Continuously challenge how we can improve our underwriting while reducing the number of questions that need to be answered in an application. Maintain a clean production environment such that the data models can be easily interpreted and built upon by other data science and engineering team members. Present your work, findings, and opinions to both technical and non-technical stakeholders. Build and support a team of data scientists and analysts to accelerate our learnings and elevate our product offerings. WE LOOK FOR TEAMMATES WHO HAVE: Bachelor/Master in a quantitative discipline (computer science, mathematics, statistics, economics, physics, engineering or related field). 3+ years of experience as a data scientist, data analyst or machine learning. Experience training machine learning models that have been deployed to execute business decisions. 5+ years experience with Python, including the typical data science stack (pandas, scikit-learn, numpy, scipy, Jupyter, etc). Strong understanding of data science metrics and methodologies for measuring model performance. Experience tracking model performance in production. Comfortable building clean, repeatable experiments in a notebook environment. Communications skills for translating technical or statistical analysis results into business recommendations. Familiarity with the tradeoffs of scaling data infrastructure and database systems. Bias to practical action and creativity using data (we value past or present projects that support this). WHO YOU WILL WORK WITH: Elizabeth Barsalou, Manager Data Scientist: Before joining Counterpart, Elizabeth worked as a full stack data scientist in small business lending for Kabbage and BHG. She specialized in building data science models, infrastructure and strategies to extend credit to small businesses. Stanley Wang, Director, Pricing Analytics: Before joining Counterpart, Stanley worked as an actuary within the pricing solutions and methods team at USAA to combine actuarial pricing with data science models. He has had many other relevant roles such as capital modeling and risk management. Newton Troung, Lead Data Engineer: Newton has almost a decade of experience in platform and data engineering. In his last company Thrive Market, he helped build new microservices and architect data pipelines with Airflow and Spark. COUNTERPART'S VALUES Conjoin Expectations - it is the cornerstone of autonomy. Ensure you are aware of what is expected of you and clearly articulate what you expect of others. Speak Boldly & Honestly - the only failure is not learning from mistakes. Be Entrepreneurial - control your own destiny. Embrace action over perfection while navigating any obstacles that stand in the way of your ultimate goal. Practice Omotenashi (“selfless hospitality”) - trust will follow. Consider every interaction with internal and external partners an opportunity to develop trust by going above and beyond what is expected. Hold Nothing As Sacred - create routines but modify them routinely. Take the time to reflect on where the business is today, where it needs to go, and what you have to change in order to get there. Prioritize Wellness - some things should never be sacrificed. We create an environment that stretches everyone to grow. WE OFFER Work from Anywhere - Counterpart is a fully distributed company, meaning there is no office. Employees work from wherever they do their best work, with meetings often scheduled in US time zones. Language Classes - We sponsor up to $100 per calendar year toward language classes to support your English language skills. Paid Vacation and Time Off Parental Leave - Development partners are eligible for up to 8 weeks of unpaid parental leave. Time off is subject to approval and must be requested at least 45 days in advance. Computer - We reimburse you for a locally procured MacBook Pro. After one year, it is yours to keep. Our estimated pay range for this role is USD $70,000 - $80,000 annually . Contractor compensation is determined by a variety of factors, including but not limited to, market data, location, internal equitability, and experience. We are committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported and connected at work—regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives. We are an Equal Opportunity Employer. We do not discriminate against qualified applicants or employees on the basis of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by federal, state, or local law, rule, or regulation. #J-18808-Ljbffr