(Closed) Lead Quantitative Analyst
PandaScore provides statistics and odds for the top esports competitions globally. We’re building the data infrastructure that will take the industry to the next level using AI and deep esports expertise. Top teams, bookmakers, fantasy apps, and media companies use PandaScore to get the best esports data. Join us and take part in building the future of esports.
Why are we doing all this? 🤷
Video games have changed the way we experience entertainment, and now esports is catching up to and in some cases, exceeding the popularity of traditional sports with younger generations. Esports is experiencing the same evolution as traditional sports has gone through over past decades, but in just a few years. The growth is truly incredible.
At PandaScore we want to help the growth of esports by providing data and odds to businesses. We want to have the most reliable and accurate data so great products can be built in esports. Our customers rely on us for fast and accurate real-time that powers millions in revenue each month. If you work at PandaScore, you truly have an impact on the entire ecosystem.
We also strongly believe that AI will revolutionize both esports and traditional sports. That’s what we’re here for.
To support PandaScore’s growth, we are looking for a Lead Quantitative Analyst!
As PandaScore’s Lead Quantitative Analyst, you will be focus on our odds product and responsible for building and improving our current prediction models by using mathematical and statistical models as well as machine learning algorithms. You’ll also be involved in R&D projects using both machine learning expertise and project management skills.
If you’re interested in combining esport & AI and want to use state of the art algorithm to process real time data, then this is the place to be.
Your missions 🏀
- Take the technical lead on all Data Science odds at Pandascore
- Mentor the data scientists odds team and support its continuous growth
- Integrate your brand new models into production in our odds engine and maintain it
- Implement innovative algorithms to allow our trading team to adjust the odds while keeping a consistent pricing
- Research new approaches to optimize the performance of all models and data science processes
- Build the tools you will need in order to achieve your goals
- Work in our strong and diverse Data Science team, in which you will take full ownership of your work
We are primarily looking for candidates who are eager to participate in the company’s evolution and take part in the growing of the esport ecosystem.
What’s in it for you 🎁
- If you’re Paris based: Central office (Ⓜ️Bonne Nouvelle) with a gaming room (PS4, PCs, Switch) with a remote friendly approach
- Possibility to be based remotely
- Other usual perks (health insurance, transportation participation, Swile card)
- Video game credits 🤘
- Work in a fast-paced, high-growth industry with innovation as our motto
- At Pandascore we want everyone to be involved in the success of the company and we reward both individual and collective efforts by offering company Stock Options (French BSPCEs)
What do you need? 💪
- Experience in modeling, probability and statistics -> time series predictions, bayesian inference, machine learning among other hot topics
- Ideally, you have an experience working with quantitative finance modelling or at a similar role or exposure to a trading department where modelling/quant data research has been practised
- 3+ years of experience as a data scientist including mentoring experience with other data scientists
- PhD or Master in statistics, data science, computer science, mathematics or a related field
- Highly proficient in Python and the main data science libraries
- Interest in esport
In short, you are: 😇
- A team player: You are a good communicator, reliable, respectful. You help people and learn from them.
- Rigorous: You care about details that actually matters
- Data-driven: You know how to make data talk to take the good decision
- Metrics-driven: You know which metric to pick for your problem, how to track it and act accordingly
- Autonomous: You can move forward on your tasks alone while asking for help or advise to the good person at the good moment
- Product-oriented: You focus on the short term and long term outcomes for the product