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Salary: USD 178,500 - 178,500 / annual
DuckDuckGo is a profitable, remote-first online protection company founded in 2008 with 300+ team members and annual revenue exceeding $100M USD. The company operates a privacy-focused search engine, browser (Mac, Windows, iOS, Android), and AI products including Duck.ai, which provides private access to ChatGPT, Claude, and other AI models.
You will join the Data Science Functional Team, driving product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, and classifier implementation. Your work will span the search engine, instant answers, AI products, and revenue optimization initiatives.
Recent team projects include: defining core growth metrics and building infrastructure to monitor trends and anomalies; measuring the impact of major marketing campaigns for Duck.ai and translating full-funnel data into actionable decisions; building monitoring pipelines to detect unexpected shifts in search traffic patterns; expanding evaluation datasets for page context understanding across complex scenarios; and improving trigger systems that determine when AI-assisted answers surface in search, balancing quality with privacy-first principles.
The role emphasizes working with privacy-constrained, necessarily sparse data in an evidence-first culture where quantitative rigor is the baseline. You will have end-to-end ownership of projects from scoping and execution to postmortem, collaborating effectively with product teams.
The company operates a remote-first model with flexible work arrangements and no core hours, though an average 40-hour weekly commitment is expected. All team members are required to attend an all-hands meetup and team retreat annually (each 4-5 days). Video conferencing is required for meetings. Background check is mandatory.
REQUIREMENTS:
- 7+ years of experience in Data Science with a track record of leading high-complexity projects from scoping to production with minimal direction
- Demonstrated expertise in 2 or more of the following: deploying and iterating on ML in production environments; developing and deploying NLP solutions; applying knowledge of LLMs including fine-tuning, LLM-as-judge, and AI-assisted development; conducting marketing campaign analysis using Bayesian methods
- Production-grade code writing in Python or comparable high-level language
- Advanced SQL and query optimization skills; familiarity with columnar databases (BigQuery, Clickhouse, Redshift, Druid)
- Experience with BI tools like Tableau or PowerBI (preferred)
- Ability to design, implement, and analyze experiments across product surfaces
- Comfort deriving insights from sparse or privacy-constrained data
- Effective collaboration with product teams and contribution to overall team throughput
