Parsyl is an insurance technology company that delivers data-driven cargo insurance solutions for essential supply chains including vaccines and medicines, perishable foods and other sensitive goods. Our mission is to end the days of “ship and pray” and build a world where everyone, everywhere can trust the quality of the goods they rely on, from the foods they eat to the medicines they need. 

We are working to achieve this by combining smart sensors, data insights, and data-driven insurance to improve risk resiliency and safeguard goods in transit and storage. This unique combination of IoT and insurance means our customers can use data to make supply chains more transparent, safe and sustainable - better for people and the planet. 

In response to the Covid-19 pandemic, Parsyl led the formation of the Global Health Risk Facility, the world’s dedicated insurance solution for distributing Covid-19 vaccines and other essential health products around the globe. 

Where you fit in:

Parsyl is disrupting traditional cargo insurance by combining world-class insurance experts, proprietary and third-party data, and machine learning and data analysis. You will be instrumental in us achieving this goal, by leading the insurance data science effort and working closely with the insurance team. You will meaningfully influence the strategic direction and the form of our data-driven insurance solutions. 

You are a good fit for this position if you have the technical expertise to build and deploy state-of-the-art machine learning solutions but choose a linear regression when appropriate. You are highly motivated and excited to collaborate with insurance, product, and the rest of the data team to build data-driven products with no precedent. 

Technologies used in this role:

• Python data science toolkit (pandas, sklearn, numpy, etc.)

• SQL

• Git

What you’ll get to work on:

• Lead the development of novel data-driven underwriting and risk management tools, evolving from descriptive statistics to predictive and prescriptive machine learning algorithms.

• Identify and evaluate publicly available and partner data, and synthesize it with Parsyl’s proprietary IoT time-series data to accelerate and enhance internal underwriting and external risk management tool development.

• Develop predictive models to identify real-world root cause phenomena, such as mis-used equipment. 

• Use natural language processing to mine claims data and systemize textual records.

• Collaborate with insurance, product and data engineering to deploy, monitor, and productize the above.

• Communicate complex concepts, solutions and analyses in a clear and effective manner to business stakeholders and technology leaders to maximize the effectiveness of data science initiatives.

• Bring technical leadership and best practices to the data science and analyst teams.

Qualifications:

• 3+ years of industry experience as a data scientist or ML engineer.

• Masters or PhD in Statistics, Computer Science, Engineering, or another quantitative discipline OR an additional 2 years of relevant experience.

• Prior experience applying machine learning to real-world data problems and deploying models to a production environment.

• Strong fundamentals in algorithms, statistics and predictive modeling.

• Excellent Python and SQL skills and experience with ML libraries.

• Creative problem solver who finds solutions in algorithms, mathematics, software, data and an understanding of the real world end need. 

• Excellent communication skills - ability to clearly articulate goals, methodologies, and results of complex projects to a diverse set of stakeholders.  

• Track record of rigorous execution and high impact.

• Self-motivated, detail-oriented, highly organized, and a team player.

• Parsyl requires all employees to be fully vaccinated against Covid-19, unless they qualify for a religious or medical accommodation.

BONUS IF YOU ALSO HAVE…

• Experience in financial industries, such as insurance, mortgages, etc.

• Experience in supply chain, global health, or perishables.

• Experience working with IoT sensor or other time series data.

Qualities We Look For:

• Mission -- You are highly motivated and inspired by our mission to improve health and save money for people across the globe.

• Grit -- You bring determination and a strong will to the challenges and opportunities that come with being at an early stage.

• High Standards -- You take pride in your work and are highly accountable. 

• Curiosity -- You are energized by finding creative solutions to new situations. 

• Self-Starter -- You are ambitious and take initiative, and thrive in environments with minimal supervision. 

• Humility -- You approach your work with humility and a willingness to collaborate and learn from those around you in order to produce the best outcome.

Compensation and Benefits:

• Market competitive salary with an anticipated base compensation range of $130,000 - $160,000. Actual salaries will vary depending on a candidate’s experience, qualifications, skills and location.  

• Early-stage stock options

• 100% of medical, dental, and vision premiums for employees and 75% of premiums for dependents based on a solid, mid-tier plan

• 401(k) including company match

• Unlimited vacation policy

• Company Breaks - quarterly mental health days, week-long summer break, two-week-long winter break

• Paid sabbatical program

• Flexible hybrid work environment

• Monthly wellness and commuter benefit

• Home office set-up benefit

• Significant career growth opportunities

• Continuing education stipend

• Relocation assistance available (Denver, CO candidates or candidates willing to relocate strongly preferred, but remote candidates will be considered)