Talent Network: Lead Data Scientist

About the Role

The day-to-day responsibilities of this role will involve designing and building Task Mining and Process Mining solutions, developing ML systems and data pipelines, and collaborating with engineering teams to deploy production-ready services. You will also communicate findings, tradeoffs, and technical concepts effectively to both technical and business stakeholders.

Toptal is a global network of top talent in business, design, and technology that enables companies to scale their teams on-demand. With $200+ million in annual revenue and team members based around the globe, Toptal offers a unique opportunity to work with a diverse group of professionals who share a passion for innovation and excellence.

What You Will Do

• Design and build Task Mining and Process Mining solutions that transform raw interaction data into discovered workflows, patterns, bottlenecks, and optimization opportunities
• Develop and deploy ML systems and data pipelines for large-scale structured, unstructured, and event/interaction data
• Build predictive and pattern-discovery solutions using supervised and unsupervised learning, representation learning, sequence modeling, and LLM/GenAI approaches
• Establish practical foundations for dataset construction, labeling strategy, offline/online evaluation, monitoring, feedback loops, and human-in-the-loop review
• Own projects end-to-end, from problem framing and experimentation through production deployment and iteration
• Collaborate closely with engineering on data instrumentation, pipeline design, deployment, and integration of production-ready services
• Communicate findings, tradeoffs, and technical concepts effectively to both technical and business stakeholders
• Act as the founding Data Scientist on the product, defining the DS strategy, choosing the right tools and frameworks, and establishing best practices
• Design, develop, and deploy ML systems and data pipelines for large-scale structured, unstructured, and event/interaction data

What We Are Looking For

• 5+ years of professional experience in Data Science, Machine Learning, or Applied ML roles
• Demonstrated experience operating as the sole or lead Data Scientist on a product or team — owning problems end-to-end without senior DS supervision
• Strong experience with supervised and unsupervised ML, modern ML/data tooling, and the judgment to select the right approach for the problem
• Practical familiarity with representation learning, sequence modeling, Transformers, LLMs, or GenAI systems where relevant to product use cases
• Experience handling large-scale structured, unstructured, event, or interaction datasets
• Advanced proficiency in Python and SQL, with hands-on experience using tools such as PyTorch, scikit-learn, pandas/Polars, experiment tracking, and production ML workflows
• Experience deploying ML models, data pipelines, or intelligent systems into production
• Familiarity with Task Mining, Process Mining, event-log analysis, behavioral analytics, workflow automation, or adjacent domains

Nice to Have

• Advanced degree in Computer Science, Data Science, AI, Statistics, Mathematics, or a related field
• Experience with cloud-based data platforms and containerization using Docker
• Familiarity with agile development methodologies and version control systems such as Git

Benefits and Perks

• Opportunity to work with a global network of top talent in business, design, and technology
• Flexible working hours and remote work arrangements
• Access to cutting-edge tools and technologies
• Professional development opportunities and support for ongoing education and training
• Competitive compensation package and benefits
• Opportunity to work on complex and challenging problems that drive business impact
• Collaborative and dynamic work environment with a team of experienced professionals
• Recognition and rewards for outstanding performance and contributions to the company,

• To stand out in the application process, create a portfolio that showcases your technical skills and experience in data science, including examples of ML models and data pipelines you have built and deployed.
• Highlight your ability to communicate complex technical concepts effectively to both technical and business stakeholders, and provide examples of times when you have done so in previous roles.
• Be prepared to discuss your experience with Task Mining and Process Mining, and how you have applied these skills to drive business impact in previous roles.
• Show a willingness to learn and adapt to new technologies and tools, and be prepared to discuss how you stay up-to-date with the latest developments in the field of data science.
• When negotiating salary, be sure to highlight your relevant experience and skills, and do not be afraid to ask for what you are worth.
• Be cautious of companies that do not provide clear information about the role, team, or company culture, and do not be afraid to ask questions during the interview process.