Talent Network: Lead Data Scientist

Toptal • Orlando, FL

6d • Remote

About The Position

We are looking for a Senior Data Scientist to join us as the first Data Scientist on a new product we are building. This is a founding role: you will shape the data science function from the ground up, set technical direction, and own the end-to-end delivery of intelligent systems that define how our product creates value. You will tackle open-ended problems involving Task Mining, Process Mining, behavioral workflow analysis, pattern discovery, predictive modeling, and applied GenAI/ML systems. The goal is not just to build models, but to turn raw interaction data into measurable product and business impact: discovered workflows, bottlenecks, optimization opportunities, and scalable foundations for future DS/ML work.
This is a remote position. We do not offer visa sponsorship or assistance. Resumes and communication must be submitted in English.

Requirements

• 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.
• Advanced degree in Computer Science, Data Science, AI, Statistics, Mathematics, or a related field is a plus; equivalent practical experience is strongly valued.

Nice To Haves

• Previous experience as a first or early Data Scientist at a startup or new product line.
• Direct experience with Task Mining, Process Mining, workflow intelligence, RPA, or productivity analytics.
• Experience with LLMs and Generative AI applications, especially evaluation, structured outputs, semantic labeling, summarization, or human-in-the-loop workflows.
• Experience working with privacy-sensitive behavioral, productivity, or user-interaction data.
• Experience with product experimentation, causal inference, or measuring the impact of workflow/process interventions.
• Knowledge of MLOps and distributed processing frameworks, such as Spark.
• Experience with cloud environments, especially GCP.

Responsibilities

• Act as the founding Data Scientist on the product: define the DS strategy, choose the right tools and frameworks, and establish best practices.
• Design and build Task Mining and Process Mining solutions that transform raw interaction data into discovered workflows, patterns, bottlenecks, and optimization opportunities.
• Design, 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 where appropriate.
• Establish practical foundations for dataset construction, labeling strategy, offline/online evaluation, monitoring, feedback loops, and human-in-the-loop review where needed.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed