Senior Data Scientist

About the role

You will own the end-to-end lifecycle of data science initiatives that directly shape product strategy and business outcomes at DuckDuckGo. You will define core growth metrics, build the monitoring infrastructure that tracks anomalies in real time, and translate sparse, privacy-constrained search and AI data into rigorous quantitative insights. You will design and analyze experiments across search surfaces, implement production-grade NLP and LLM-based classifiers, and measure the full-funnel impact of marketing campaigns for Duck.ai. You will balance the deployment of AI-assisted answers in search with our privacy-first ethos, ensuring that every model and trigger system meets our high standards for quality and trust. Across all projects, you will collaborate closely with product teams to scope work, drive execution, and own postmortems, delivering actionable decisions from first principles evidence.

Key facts

What you'll do

Define core growth metrics for our products and build the infrastructure to monitor trends and anomalies across search, instant answers, AI features, and revenue optimization.

Measure the impact of major marketing campaigns for Duck.ai, translating full-funnel data into actionable decisions using Bayesian methods and rigorous experiment design.

Build monitoring pipelines to detect unexpected shifts in search traffic patterns faster and more reliably, enabling proactive responses to product issues.

Expand evaluation datasets for page context understanding across complex scenarios like multi-tab browsing, content reattachment, and evolving query intent.

Improve the trigger systems that determine when AI-assisted answers surface in DuckDuckGo Search, balancing answer quality with our privacy-first approach and user trust.

Deploy and iterate on machine learning models in production environments, ensuring reliability, scalability, and compliance with our privacy constraints.

Develop and deploy natural language processing solutions that enhance search understanding, instant answers, and AI features while maintaining rigorous performance benchmarks.

Apply knowledge of large language models, including fine-tuning, LLM-as-judge evaluations, and AI-assisted development practices to improve product outcomes.

Conduct statistically sound experiments across product surfaces, deriving insights from sparse or privacy-constrained data and communicating results to cross-functional stakeholders.

Collaborate effectively with product managers, engineers, and analysts to prioritize projects, align on metrics, and contribute to overall team throughput and roadmap execution.

Write production-grade code in Python or a comparable high-level language, emphasizing maintainability, reproducibility, and robustness in data pipelines and models.

Leverage advanced SQL and query optimization skills on columnar databases such as BigQuery, Clickhouse, Redshift, or Druid to support fast, accurate analysis at scale.

Utilize business intelligence tools like Tableau or PowerBI to visualize complex data patterns, enabling clearer decision-making for product and executive stakeholders.

Design and implement evaluation frameworks that assess page context understanding, search relevance, and AI answer quality under real-world privacy constraints.

Champion an evidence-first culture by structuring analyses around quantitative rigor, clear assumptions, and reproducible methods that stand up to peer review.

Take ownership of your projects from scoping and initial hypothesis through execution, monitoring, and postmortem learning, ensuring end-to-end accountability.

Requirements

You have 7+ years of experience in Data Science with a track record of leading high-complexity projects from scoping to production with minimal direction.

You can do 2 or more of the following: deploy and iterate on ML in production environments, develop and deploy NLP solutions, apply knowledge of LLMs including fine-tuning and LLM-as-judge, and conduct marketing campaign analysis using Bayesian methods.

You write production-grade code in Python or a comparable high-level language, emphasizing clean design, testing, and documentation.

You have advanced SQL and query optimization skills, with familiarity with columnar databases such as BigQuery, Clickhouse, Redshift, or Druid.

Experience with a BI tool like Tableau or PowerBI is a plus, as is demonstrated ability to visualize complex analytical results for diverse audiences.

You can design, implement, and analyze experiments across product surfaces, and you are comfortable deriving insights from sparse or privacy-constrained data.

You collaborate effectively with product teams and contribute to overall team throughput by aligning on priorities, communicating clearly, and delivering actionable insights.

You have a strong grasp of statistical methods, experimental design, and causal inference, and you apply these principles to evaluate product changes and marketing impact.

You are comfortable working with large-scale data pipelines and ML workflows, ensuring that models remain performant, reliable, and aligned with privacy constraints.

You communicate findings clearly to both technical and non-technical stakeholders, translating data insights into decisions and actions.

You are proactive in identifying opportunities to improve data quality, monitoring, and tooling, and you take initiative to drive improvements across the data stack.

You demonstrate ownership and accountability by seeing projects through from implementation to postmortem and by mentoring peers where appropriate.

Practical notes

Hiring works best when it is a two-way street. You will get to know DuckDuckGo, envision your future role here, and find out more about how we hire at https://duckduckgo.com/how-we-hire.

You'll be required to sign an NDA and to adhere to our strict no-tracking policy in all of our products and services.