Required Data Science Team Lead
About the Role:
The Data Science department plays a pivotal role in our company, generating value for us by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to extract maximum value from data of all shapes and sizes, including classification models, NLP, anomaly detection, graph theory, deep learning, and more.
Our models and algorithms are integrated into the critical path of our product, helping to make thousands of decisions per second in real-time. All the capabilities we develop must meet production-grade requirements in both analytical and engineering standards.
As the Team Lead of a Data Science team, you will manage critical analytical initiatives for our suite of products, shaping the team's direction and focus. You will collaborate closely with Product Managers to influence the future of our product offerings and ensure alignment with company goals. You will need a holistic view of our challenges and a keen understanding of the underlying goals of the department and company. In this role, you will lead the team, oversee their professional development, build effective collaborations with other departments, and bring measurable value to our product through your team's efforts.
What You'll Be Doing:
Lead and manage a team of 3-5 Data Scientists
Collaborate closely with the Dev, Product, and Analytics teams to implement and successfully integrate models and capabilities into production
Play a pivotal role in shaping the vision for the analytical capabilities of our core products
Constantly experiment with new ways to improve our product offering, including complex experimental design
Oversee the training of our strategic models
Lead the research and development of core product Machine Learning capabilities
Standardize processes and methods used within the team and group.
Requirements: 3+ years experience as a team lead of a data science team, managing at least 3 ICs
3+ years proven hands-on IC experience implementing machine learning algorithms and techniques in production grade environments
M.Sc in Statistics, Computer Science, Mathematics, or a related field
Strong foundation in ML theory and statistical modeling, with proven experience in supervised learning at scale, complex feature engineering, and optimizing labeling strategies for imbalanced datasets.
Proven track record of translating business KPIs into technical roadmaps and measurable data science objectives.
Ability to lead by example by contributing high-quality code and taking a hands-on role in resolving critical technical challenges and bottlenecks.
Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment
Experience in defining long-term research strategies and managing technical debt within an agile DS framework.
Experience in the fraud domain - advantage.
This position is open to all candidates.