Data Science Team Lead

What Relocity is Doing 

Relocity is reimagining the global mobility experience. We enable enterprises to attract, retain, and engage talent globally. Powered by our AI-driven workforce mobility platform, we bring together local experts and insightful content in our native mobile app to deliver an excellent user experience for people on the move. Our core values drive us to focus on our customers, innovation, integrity, and excellence. Relocity serves hundreds of cities in more than 40 markets across the United States, Europe and Asia. Learn more at www.relocity.com.

What You’ll Do…

Relocity is seeking a Data Science Team Lead who will guide the development of our AI-driven mobility platform by leading a team of Data Scientists and collaborating closely with Data Engineers. You will be responsible for the end-to-end design and implementation of machine learning models and data science solutions that support our global mobility platform. You will work closely with stakeholders to understand business requirements, architect scalable solutions, and drive data-driven innovation. Your technical leadership will be key to ensuring that Relocity stays at the cutting edge of AI and data science, delivering insights that improve the overall customer experience.

This role reports to the Chief Technical Officer.

How You’ll Do It…

• Technical Leadership for Global Mobility Solutions: Lead the technical execution of data science projects specifically tailored to solving challenges in the global mobility space, ensuring that AI and machine learning solutions enhance our platform’s ability to support enterprises and their globally mobile workforces.
• Personalization through AI: Develop AI models that deliver relevant, tailored content to transferees based on their profile (e.g., family type, relocation needs) and journey stage, ensuring a personalized and engaging experience.flows, predicting relocation outcomes, and improving user engagement with our platform.
• Optimizing Workflows: Design intelligent systems that optimize relocation processes, predict outcomes, and enhance user interaction, providing timely, personalized recommendations throughout the relocation journey.
• AI-Driven User Interaction: Collaborate with product and engineering teams to integrate innovative AI solutions into user-facing tools, enabling transferees to access deeper, personalized information seamlessly during their relocation.
• Optimize Data Pipelines: Ensure data pipelines and models are optimized for large-scale data sets related to global mobility, focusing on performance, scalability, and predictive accuracy to support enterprise needs.
• Actionable Insights for Mobility Strategy: Use advanced analytics to uncover trends in global mobility, providing actionable insights that help streamline relocation processes and improve user engagement for enterprises.
• Maintain Data Integrity and Governance: Work with the data engineering team to ensure that the data powering global mobility solutions is accurate, secure, and complies with all relevant regulations.
• Stakeholder Communication on Mobility Impact: Clearly present technical solutions and data-driven insights related to global mobility challenges to both internal stakeholders and external clients, ensuring alignment with business objectives
• Dynamic Environment & Continuous Learning: Thrive in a dynamic environment by maintaining clear communication and demonstrating patience. Show curiosity by continuously learning about the product and adapting to new challenges. Emphasize timely delivery and high-quality results while effectively managing stakeholder expectations.

What Past Experience and Current Skills Will Enable Your Success In This Role?

• Minimum of 7+ years of experience in data science, with at least 3+ years in a technical leadership or similar role.
• Machine Learning Expertise: Strong knowledge of machine learning algorithms, statistical modeling, and predictive analytics, with a track record of building and deploying models in production environments.
• Data Science Tools & Technologies: Expertise in Python, R, SQL, and data science libraries (e.g., TensorFlow, XGBoost, Scikit-learn), as well as experience with cloud platforms like AWS, GCP, or Azure.
• Leadership & Mentorship: Proven experience leading and mentoring Data Science teams, guiding them in the development of robust, scalable solutions.
• Problem-Solving & Innovation: Ability to tackle complex problems, identify innovative solutions, and apply advanced analytical techniques to real-world use cases.
• Collaboration & Communication: Strong communication skills, able to work effectively with both technical and non-technical stakeholders.
• Project Management: Experience managing multiple projects simultaneously, ensuring timely and successful delivery of data science solutions.
• Data Engineering Collaboration: Familiarity with data engineering concepts and the ability to work closely with Data Engineers to build scalable data pipelines.
• Master's Degree in Data Science, Computer Science, or a related field; PhD preferred.

These are Nice-to-Haves…

• Experience in Global Mobility or Workforce Management Platforms
• Experience in both startup and corporate environments
• Knowledge of AI-driven SaaS solutions

Pay Range: $180,000-$200,000k plus Bonus

How We Support You and Work Life Balance…

• Competitive Compensation
• Paid Time Off
• Paid Parental Leave
• Remote Workplace
• Flexible Work Schedules
• Health, Dental, Vision, LTD Insurance
• 401(k)
• Professional Development Opportunities

Relocity is an Equal Opportunity Employer and does not discriminate against any applicant on the basis of race, color, religion/creed, national origin, gender, or sex, marital status, age, disability, use of a guide dog or service animal, sexual orientation, military/veteran status, or any other status protected by Federal or State law or local ordinance. Relocity will only employ those who are legally authorized to work. Any offer of employment is conditioned on the successful completion of a background investigation.

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