Lead Data Scientist

As Lead Machine Learning Engineer, you will collaborate with an industry-leading team and enhance your skills in delivering groundbreaking solutions to continue driving innovation at.

This role follows a hybrid approach to working, allowing you to combine working from home with working in our modern offices. Our modern office space is equipped with working and leisure areas, meeting rooms and sufficient space suitable for workshops and training sessions for larger groups. We regularly host social and well-being events. With in-house snacks, meal, fruit and drinks, (with in-house Free meal to all employees), office has stylish art and photography crafted to convey the energy and excitement of a gaming experience, our office in Hyderabad, India is perfect for our growing community of employees.

What You Will Do

Across areas such as Sports Betting, Gaming, and other products, you will lead the development of advanced machine learning solutions bringing to bear our vast data assets.

You will have the opportunity to develop advanced ML Engineering solution to streamline AI solutions, deploying a variety of algorithms in production and set ML-Ops standard together with the Data Scientists.

You will work with diverse teams to become an architect of innovation with AI, driving the company's strategic edge by transforming raw data into actionable insights in this dynamic and thrilling environment.

What You Will Need

• A Master’s degree qualified in a STEM subject along with more than 8 years of experience as a Data Scientist or ML Engineer.
• Previous experience in leading a team of ML Engineers and Data Scientists
• An understanding that a team is greater than the sum of its parts and embraces winning together.
• Ability to work with minimal supervision.
• Proficiency in Python programming language and a deep understanding of statistical and machine learning techniques.
• Experience manipulating large datasets using SQL and Pyspark.
• Experience with “Big Data” platforms (Google Cloud, Amazon Web Services, Azure, Oracle Cloud) and engines (Apache Hadoop, Apache Kafka, Apache Spark)
• Experience delivering several production grade machine learning products in an academic or corporate environment is crucial.
• Hands-on experience in ML Techniques, such as tree-based learners, deep learning (e.g. CNNs, RNNs, GNNs & Transformers), reinforcement learning and/or unsupervised methods.
• Exposure to cloud-based machine learning solutions
• Ability to Manage ML-Ops lifecycle (deploy-monitor-maintain-evolve)
• Knowledge of ML-Ops/DevOps technology (Docker, Kubernetes, CI/CD pipeline…)
• Excellent abilities to tell a story through data and explain technical concepts to partners.