Lead Data Scientist

As a Lead Data Scientist at Upwork, you will be a key member of the centralized Data Science team within the Finance organization. You will drive analytics and modeling to power Upwork’s growth and marketplace efficiency, leading high-impact projects from problem framing to model development and actionable insights. This role involves advancing core data science work, building scalable frameworks, and partnering with stakeholders to deliver measurable impact across domains like search relevance, pricing, and risk. It blends technical depth with leadership, mentoring peers and elevating analytical rigor.

Must Have

• Lead data science initiatives from exploration through delivery, defining metrics and success criteria.
• Develop statistical and machine learning models to optimize marketplace systems.
• Build and maintain high-quality feature pipelines with clear data contracts, lineage documentation, and data-quality monitoring.
• Set up and improve DS workflows: experiment tracking, reproducibility, and CI/CD practices.
• Mentor peers through code reviews, model evaluations, and collaborative problem solving.
• Translate complex analyses into insights that influence product, finance, and executive decisions.
• 5+ years of experience in Data Science, Applied Science, or a similar role delivering data-driven solutions at scale.
• Advanced Python and SQL skills, including data manipulation (pandas, NumPy, scikit-learn) and workflow tools (Airflow, Dagster, Spark).
• Comfort working with modern AI-assisted coding tools (e.g., ChatGPT, Cursor, Gemini).
• Deep understanding of experimentation and statistical evaluation, with a focus on actionable business impact.
• Hands-on experience with model development and evaluation, including feature engineering, calibration, and error/bias analysis.
• Practical MLOps expertise—implementing experiment tracking, reproducibility practices, environment management, containerization (e.g., Docker), version control, and leveraging feature stores or model registries.
• Collaborative communicator who thrives in cross-functional environments and enjoys mentoring others while staying hands-on with the work.
• Must be within reasonable commuting distance of Toronto and report to an office 3 days per week.

Good to Have

• Familiarity with dashboarding tools such as HEX and Tableau.

As a Lead Data Scientist, you’ll be a key member of our centralized Data Science team within the Finance organization, driving the analytics and modeling that power Upwork’s growth and marketplace efficiency. You’ll lead high-impact projects end-to-end—framing ambiguous problems, developing robust models, and turning insights into actionable decisions across domains like search relevance, pricing, macro-impact on business, supply-demand balance, and risk.

You’ll spend most of your time advancing core data science work: exploratory data analysis, model design, feature engineering, and experimentation. The rest of your focus will go toward building the frameworks, tools, and workflows that make Data Science scalable—accelerating experimentation, improving data quality, and ensuring our analytical systems are trusted and repeatable. This role will partner closely with stakeholders across the business to understand their goals, uncover pain points, and translate those needs into actionable data science solutions. You’ll take ownership of a key problem space, driving clarity on problem definition, scoping opportunities, and executing the technical work end-to-end to deliver measurable impact.

This role blends technical depth with influence and leadership. You’ll create clarity across functions, mentor data scientists, and raise the bar for analytical rigor and impact while staying close to the data yourself.

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Responsibilities:

• Lead data science initiatives from exploration through delivery, defining metrics and success criteria that connect your work to measurable business outcomes.
• Develop statistical and machine learning models to optimize marketplace systems such as search, pricing, and recommendations, conducting rigorous offline experimentation to select features, tune hyperparameters, and validate model performance.
• Build and maintain high-quality feature pipelines with clear data contracts, lineage documentation, and data-quality monitoring in collaboration with Data Engineering and Infrastructure.
• Set up and improve DS workflows: experiment tracking, reproducibility, and CI/CD practices that shorten time-to-insight and strengthen reliability.
• Mentor peers through code reviews, model evaluations, and collaborative problem solving, helping elevate the team’s technical standards.
• Translate complex analyses into insights that influence product, finance, and executive decisions.

What it takes to catch our eye

• 5+ years of experience in Data Science, Applied Science, or a similar role delivering data-driven solutions at scale.
• Advanced Python and SQL skills, including data manipulation (pandas, NumPy, scikit-learn) and workflow tools such as Airflow, Dagster, or Spark. Familiarity with dashboarding tools such as HEX and Tableau is a strong plus.
• Comfort working with modern AI-assisted coding tools (e.g., ChatGPT, Cursor, Gemini) to accelerate development, prototype faster, and iterate on ideas (a.k.a vibe-coding).
• Deep understanding of experimentation and statistical evaluation, with a focus on actionable business impact.
• Hands-on experience with model development and evaluation, including feature engineering, calibration, and error/bias analysis.
• Practical MLOps expertise—implementing experiment tracking, reproducibility practices, environment management, containerization (e.g., Docker), version control, and leveraging feature stores or model registries.
• Collaborative communicator who thrives in cross-functional environments and enjoys mentoring others while staying hands-on with the work.

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This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub. Once the hub is established, there may be opportunities to transition to employment with Upwork depending on business needs and other requirements. While employed by the partner, you’ll work as part of Upwork’s team, with access to our resources, culture, and growth opportunities.

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