Machine Learning Product Manager
Akur8, France
Job Description
Akur8 is a young, dynamic, fast growing Insurtech startup that is revolutionizing insurance pricing with transparent AI.
Since 2016 our skilled Ramp;D team of Data Scientists, Software Engineers and Actuaries has developed unique AI algorithms that automate the insurance pricing process in an unprecedented way.
Our solution is a SaaS platform which allows insurance companies to model their risks 10 times faster, with a higher predictive power than traditional methods. constituting a major game changer for the insurance industry.
Akur8 has been already been selected:
- In CB Insights Top 50 World Insurtech Companies 2022
- In Fintech Global’s Top 100 AIFinTech list 2022
- As No.24 in Sønr’s World Top 100 Insurtech Companies 2022
- As 3rd best overall (worldwide) in the CodinGame 2022 Software Engineering Fall Challenge
With 31 nationalities within our team, and offices in Paris, London, New York, Tokyo, Milan amp; Cologne, Akur8’s solution is international by design. Servicing 85 clients across 3 continents and targeting all non-life insurance carriers, we focus on more mature markets for faster expansion.
To learn more about Akur8, and what we do, click here.
Akur8 is, in all senses of the term, an equal opportunities employer. Akur8 puts diversity and inclusion at the heart of its values. We examine all applications based on equal skills and applying the principles of non-discrimination.
Insurance pricing is a complex process encompassing statistical modeling, visualizations and team collaboration.
Akur8 software strives to increase efficiency, performance and transparency of the pricing workflow, designing flexible modules and processes leveraging our proprietary machine learning algorithms.
As optimal machine learning models should be intuitive, easy to test and analyse - in order to identify errors - our Machine Learning Product Managers conceptualize key features, empowering the actuary of the future whilst simultaneously upskilling and eliminating pitfalls for the end user.
Driving our innovation, the Machine Learning Product Manager influences decisions regarding the different components of our product (whether independently or as part of a committee, according to strategic importance).
A cross-functional role, providing a wide range of interactions with various internal teams (Design, Ramp;D, Sales, Marketing), it requires knowledge of how the different parts of our platform interact (something that you’ll gain both during your onboarding period and on an ongoing basis).
Furthermore, it involves discussions with our clients, understanding their needs and - as a consequence - our value proposition and opportunities for product evolution.
Over time, you’ll gather market information, extract the relevant elements and schedule the planning of product development to the next level, including:
- Being a driving force for a whole product section
- Focusing on the ‘why’ behind building features, and being able to prioritize
- Cultivating a product-oriented culture within the company
Main responsibilities:
- Constantly acquiring a deep understanding of pricing techniques
- Designing clean solutions and develop plans for successful delivery
- Conducting experiments with internal teams and partners
- Prioritizing and scoping features for internal development squads
- Animating training sessions for clients, prospects and colleagues
Requirements
For this key role within our Product Management team we’re keen to speak to applicants that meet the following criteria. You have:
- A Masters degree or PhD in a quantitative discipline
- 3+ years experience in the Machine Learning field as ML/Data Science Product Manager, ML Software Engineer, Data Scientist.
- A sound understanding of machine learning concepts, models, and algorithms
- An understanding of predictive modeling (prioritizing strategy amp; planning to build intuitive solutions amp; processes that answer client needs)
- Very strong focus on both ML validation techniques (i.e. performance metrics, model selection, PDP, etc.) and statistical concepts (i.e. regression, p-values, etc.)
- Excellent quantitative and analytical skills
- Effective communication skills (to exchange with both technical amp; non-technical stakeholders / clients).
- An ability to learn quickly to reach the required understanding of insurance pricing and provide added value to end customers