Sr. Data Scientist, Marketing and Acquisition at Clearcover
Our Value Proposition: Clearcover is a venture-backed technology start-up disrupting the trillion dollar legacy insurance market. We’ve focused on building products that create confident, happy customers - and we’re flourishing. We believe in putting our people first, paying them well and working together to solve tough problems. If you’d like a high-growth opportunity with an award-winning company, let’s chat.
What is a Sr. Data Scientist, Marketing and Acquisition at Clearcover?
Clearcover has an enormous range of opportunities around data science and machine learning ranging from marketing and acquisition, fraud detection, customer experience, and claims payment. As a Sr. Data Scientist, you will work closely and independently with our business partners, product teams, data engineers, and machine learning engineers to build and deploy machine learning and AI models to create and deliver real and measurable value for our customers. You will lead, coach, and mentor more junior data scientists while working independently on complex data science problems. We’re looking for someone curious and passionate about data and machine learning and using them to solve real world problems.
What will you do?
- Lead, coach, and mentor junior data scientists
- Review machine learning models and code
- Work with our product managers and business stakeholders to identify and scope the highest value data science problems
- Explore and understand our data and how they can feed production-grade machine learning models
- Proactively utilize data and business understanding for feature engineering
- Build, prototype, and deploy state-of-the-art machine learning models to solve real business problems
- Communicate, interpret, and explain modeling output to stakeholders
- Measure value of the machine learning models we deploy
What do you need?
- 3+ years of professional experience working as a data scientist
- Experience mentoring, managing, or leading data scientists
- Experience reviewing others’ models and code
- Expertise in building and deploying machine learning models that have been adopted or implemented, and achieved measurable value
- Experience using the Python data science stack; including pandas, scikit-learn, NumPy, XGBoost, notebook environments, etc.
- Experience with Python, including object-oriented programming
- Knowledge of SQL, including Snowflake or similar systems
- Expertise with different types of machine learning techniques
- Strong conceptual understanding of machine learning applied to real-world data, including the ability to identify and articulate modeling and data issues
- Ability to work in and lead teams
- Ability to quickly learn and keep up with the latest ML and AI technology
- Ability to effectively communicate technical concepts to non-technical audiences
Nice to Haves?
- Experience working in insurance, marketing, or fraud
- An advanced degree
But wait, there’s more: As a people-first company, your health and well-being is a priority at Clearcover. While we do offer medical (and cover the vast majority of the premium), dental, vision (and cover 100% of those premiums) and 401K (we contribute 3% even if you contribute nothing), we’ve curated a stack of perks and benefits that stretch beyond the expected. With over half of our employees remote to the Chicago HQ office, we paved the way for flexible work locations and continue to offer this flexibility. Our people also have access to unlimited vacation, monthly mental health workshops, discounted gym memberships, equity in the company and an annual bonus program. Plus, if Clearcover is available in your state, you could have access to an employee discount on auto-insurance! Excited to learn more? Complete the application below!
Clearcover is an Equal Opportunity Employer (EOE) that welcomes and encourages all applicants to apply regardless of age, race, color, religion, sex, sexual orientation, gender identify and/or expression, national origin, disability, veteran status, marital or parental status, ancestry, citizenship status, pregnancy or other reasons prohibited by law.