
Senior Data Scientist
Sporty
Employment Type
Full Time
Location
Dubai
Experience
Senior
Requirements
Job Description
Sporty's sites are some of the most popular on the internet, consistently staying in Alexa's list of top websites for the countries they operate in
As a Data Scientist at Sporty, you will play a vital role in developing innovative data science solutions and machine learning models to drive business impact. Working closely with our Trading, Product, and Tech teams, you will leverage your expertise to tackle a wide range of business challenges, translating them into supervised and/or unsupervised learning problems.
Who We Are
Sporty Group is a consumer internet and technology business with an unrivalled sports media, gaming, social and fintech platform which serves millions of daily active users across the globe via technology and operations hubs across more than 10 countries and 3 continents.
The recipe for our success is to discover intelligent and energetic people, who are passionate about our products and serving our users, and attract and retain them with a dynamic and flexible work life which empowers them to create value and rewards them generously based upon their contribution.
We have already built a capable and proven team of 300+ high achievers from a diverse set of backgrounds and we are looking for more talented individuals to drive further growth and contribute to the innovation, creativity and hard work that currently serves our users further via their grit and innovation.
Responsibilities
Create data science solutions to address a variety of business challenges that can be translated to supervised and/ or unsupervised learning problems using statistical and machine learning models
Participate in monitoring and evaluation of performance of existing models
Develop advanced quantitative models and concepts, such as LTV models, churn models, and recommendation engines
Collaborate with global teams of developers, traders and product developers to better understand business requirements and deliver end product to the clients
Implement and test the researched fixed income models using the risk research data
Liabilities and probabilities calculations
Knowledge sharing and methodological supervision of more junior team members
Requirements
Be based in European or Pan-Asian Regions
4+ years of experience as a data scientist, quantitative researcher, quantitative analyst or another relevant role.
Experience working Apache Spark
Experience working in AWS or similar cloud platforms (Azure GCP)
Advanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch, SHAP)
Knowledge of SQL and experience with relational databases e.g. MySQL
Ability to come up with sound research designs and make methodological choices to address business problems with appropriate statistical and machine learning models
Ability to critically evaluate and find flaws in existing data science solutions
Strong knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods
Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g., random forests), support vector machines, PCA, clustering models, matrix factorization, deep learning, etc
Experience using statistical and machine learning models to contribute to key business outcomes
Experience working on predictive algorithms within a ML environment
Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering
Nice to have
PhD or Master’s degree in applied mathematics, Computer Science, Financial Engineering, Technology or Engineering
Experience with Apache Airflow
Exposure to wider Data Science tools
Relevant knowledge or experience in the sports gaming industry
Benefits
Quarterly and flash bonuses
We have core hours of 10am-3pm in a local timezone, but flexible hours outside of this
Education allowance
Referral bonuses
28 days paid annual leave
2 x annual company retreats (Lisbon + Dubai in 2022 / Phuket in Q2 2023 + 1 more TBC!)
Highly talented, dependable co-workers in a global, multicultural organisation
Payment via world class online wallet system DEEL
Top of the line equipment supplied by market leader Hofy
We score 100% on The Joel Test
Our teams are small enough for you to be impactful
Our business is globally established and successful, offering stability and security to our Team Members
Our Mission
Our mission is to be an everyday entertainment platform for everyone
Our Operating Principles
1. Create Value for Users
2. Act in the Long-Term Interests of Sporty
3. Focus on Product Improvements & Innovation
4. Be Responsible
5. Preserve Integrity & Honesty
6. Respect Confidentiality & Privacy
7. Ensure Stability, Security & Scalability
8. Work Hard with Passion & Pride
Interview Process
HackerRank Test
Remote video screening with our Talent Acquisition Team + live ID check
Remote 90 min video interview loop with 3 x Team Members (30 mins each)
Pre offer call with Talent Acquisition Team
ID check via Zinc & 2 References from previous employers
24-72 hour feedback loops throughout process
Working at Sporty
The top-down mentality at Sporty is high performance based, meaning we trust you to do your job with an emphasis on support to help you achieve, grow and de-block any issues when they're in your way.
Generally employees can choose their own hours, as long as they are collaborating and doing stand-ups etc. The emphasis is really on results.
As we are a highly structured and established company we are able to offer the security and support of a global business with the allure of a startup environment. Sporty is independently managed and financed, meaning we don’t have arbitrary shareholder or VC targets to cater to.
We literally build, spend and make decisions based on the ethos of building THE best platform of its kind. We are truly a tech company to the core and take excellent care of our Team Members.
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