Data Science / ML Engineer
Who we are:
We’re on a mission of “Helping sports fans enjoy watching their favourite sports”.
Kero focuses on building proprietary algorithms that ingest real time play by play sports data and output curated in-game micro betting markets every 30 seconds that deliver an instant gratification betting experience. Our thesis is that sportsbetting products of the future will need to incorporate the same ingredients that make today's mass consumer technology popular. They are: instant gratification, social, and most importantly "mindless consumption". We built this solution and whitelabel it to operators as a next-gen sportsbetting product, allowing them to expand their TAM to casual fans and engage/retain/monetize existing users with a differentiated offering which mirrors slots more than it does traditional sports betting. How we productized over the last two and a half years was by working with pro sports teams across every major US league and NCAA, deploying the technology as a free to play module within their apps.
Simply put, Kero Sports is the ideal place to work if you are a talented professional who loves sports and is hungry for growth.
We are hiring a Machine Learning Engineer to be involved in designing and building a recommendation system based on live sports data systems focused on live time betting in sports. In this role you will implement machine learning infrastructure to understand what thousands of sports fans want to bet on while watching their favourite team play. We are excited to welcome someone who is passionate about cutting edge research in machine learning and sports. We want an individual who is able to keep up to date with the ever expanding field of Machine Learning Operations. This is a role where we both expect to learn from you and have you learn from us!
What we're looking for:
- Excellent communication skills (especially important in our current remote-work environment)
- Strong base in statistical modeling, machine learning, and regression analysis; knowledge of standard CI/CD tools
- Experience in the areas of Contextual Bandit Algorithms, Reinforcement Learning and Recommendation Systems
- Knowledge of a machine learning library such as PyTorch, Pandas, Numpy, Tensorflow, etc.
- Completion of or current enrollment in a B.S./M.S. in Computer Science, Data Science, Machine Learning, or a related technical field.
- (Preferred) Project Experience in ML, agent-based modeling, or network analysis
- Bachelor’s or Master's degree in Computer Science or related field with 2+ years of professional experience
- Knowledge of and passion for sports
While experience is important, if you think you can outperform someone with more experience and don’t have it, we’re open to chat. A willingness to take on ownership of the outcomes of your work is most important.
We welcome applicants of any educational background, gender identity and expression, sexual orientation, religion, ethnicity, age, socioeconomic status, disability, and veteran status.
How we work:
We’re a distributed company with a mission of “Helping sports fans enjoy watching their favourite sports”. Our founders, employees and contractors are all working from home all around the world. We offer fully flexible working arrangements to suit your lifestyle and circumstances.
- Learn from a world class team leading the space
- In 6 months you’ll learn more than other people learn in 3 years
- Essentially unlimited self improvement budget (online courses, and other educational experiences)
- Retreats (usually at major sporting events)
- Flexible working hours
- Flexibility to work from anywhere in the world
- Performance incentives
- You name it. We're willing to get creative to attract the right fit.
Something looks off?