Data Analytics Team Leader, Forensics (Stoke)

Overview

Data Analytics Team Leader, Forensics (Stoke) – bet365 Stoke-On-Trent, England, United Kingdom

Hiring for the technology department of the world\’s favourite online sports betting brand!

As a Data Analytics Team Leader, you will play a critical role in guiding a team of data professionals tasked with providing insights and solutions, to protect our online Sportsbook platform. Forensic monitoring supports key operational teams by capturing and analysing thousands of events per second and identifying patterns of user behaviour. The team is responsible for maintaining the health and stability of our core website, which is crucial to providing the best possible customer experience.

In this role, you will lead a team of data professionals, leveraging cutting-edge technologies at scale to develop data-intensive products for our customers. You will take ownership of our bespoke forensics’ platform, collaborating closely with senior leadership to ensure alignment between vision and execution. Additionally, you will mentor and nurture analysts within the team, fostering their growth and development.

This position provides an opportunity to shape the strategic direction of the team as we continue to evolve and tackle new and complex challenges in this field.

This role is eligible for inclusion in the Company’s hybrid working from home policy.

Preferred Skills, Qualifications and Experience

• Proven experience leading and managing a data analytics team in the delivery of complex, large-scale projects, with a strong focus on machine learning and data science applications.
• Strong understanding of statistical modelling, machine learning, data mining, and other analytical techniques, including experience with various machine learning algorithms and techniques, such as classification, regression, clustering, and deep learning.
• Significant experience in analysing and manipulating large datasets using Python and SQL, with experience using machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
• Experience with big data technologies such as Hadoop and Spark.
• Solid understanding of relational database design and development, such as PostgreSQL.
• Strong proficiency in Linux and GNU environments, including command-line tools and scripting such as Bash, or Python.
• Exceptional analytical and problem-solving skills, with the ability to quickly assess complex situations, identify root causes, and develop effective solutions.
• Excellent communication, interpersonal, and presentation skills, with the ability to explain complex concepts to both technical and non-technical audiences.
• Experience managing projects in JIRA.
• Experience in delivery planning, backlog grooming, and iterative development is desirable.

Main Responsibilities

• Leading and managing a team of data analysts in the design, development, and implementation of data analytics solutions to support our online Sportsbook platform.
• Providing technical guidance and mentorship to team members, fostering a culture of continuous learning, knowledge sharing, and technical excellence.
• Working closely with key stakeholders to understand their needs and develop data-driven solutions to address their challenges.
• Developing and maintaining a strong understanding of the data landscape, including data sources, data quality, and data governance.
• Overseeing the development and implementation of analytical models for fraud detection, risk analysis, anomaly detection, and other key areas.
• Ensuring the accuracy, reliability, and validity of data analysis and reporting, including the evaluation and validation of machine learning models.
• Communicating findings and recommendations to stakeholders, including senior management and non-technical audiences, through clear and concise presentations and reports.
• Identifying and resolving barriers to the team\’s progress, creating a smooth and efficient workflow.
• Evaluating and improving team processes, workflows, and tools to enhance overall efficiency, productivity, and data quality.
• Facilitating planning sessions, collaborating with stakeholders to refine and prioritise the product backlog, and ensuring alignment between data analytics efforts and Business objectives.

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