Data Scientist - DyDx
At a glance
Mid-level Data Science role at deCircle. Remote, United States · full-time · no salary stated · we estimate $137,581–$208,900.
deCircle has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Use SQL and Mode to turn campaign plans, lifecycle activity and product usage into insights for growth teams
- Trace funnel, campaign and cohort results to find what drives user acquisition and retention
- Run attribution work across marketing channels and assess tests and lifecycle tactics for conversion and engagement
- Build warehouse models and pipelines for marketing reporting, blockchain activity, order books and market participants
- Maintain marketing KPI dashboards, check data quality and help teams use trustworthy metrics
What you bring
- A quantitative or related degree, plus at least four years in data science, analytics, product analysis or a similar discipline
- At least two years working with blockchain or order book data, such as indexing blocks or analyzing exchange market data
- Strong SQL, database, cloud database and reporting skills, alongside Python proficiency
- Knowledge of ETL, data modeling and warehouse principles, with experience using visualization to explain findings
Who this fits
This mid-level role suits someone who can combine growth analysis with hands-on data infrastructure work. You’ll collaborate with marketing and other teams, and help teammates interpret metrics.
From the employer
At dYdX you'll have an opportunity to build state-of-the-art decentralized technologies that will redefine global financial markets. By joining us at this stage in our growth, you will help make fundamental decisions that will shape the course of dYdX.
→ Learn more about working at dYdX
RESPONSIBILITIES:
Growth Analytics
Collaborate closely with marketing and other cross-functional teams to understand campaign strategies, lifecycle efforts, product usage metrics, and translate those into actionable data insights using tools like SQL and Mode
Analyze growth funnels, campaign performance, and user cohorts to identify key acquisition and retention drivers to inform product decisions
Own attribution and cohort analyses across marketing channels to optimize user acquisition strategy
Design and evaluate A/B tests and lifecycle marketing strategies to improve user conversion and engagement
Data Infrastructure & Enablement
Design and maintain scalable data pipelines and structured models in the data warehouse (e.g., using SQL) to power marketing dashboards, campaign tracking, and self-serve analytics
Build pipelines for blockchain transaction, order book, and market participant data to support analysis of user behavior, product engagement, and market dynamics relevant to growth strategies
Own and evolve marketing dashboards with KPIs, data visualization with strong story telling, etc. to influence marketing and product decisions for Senior Leadership
Ensure high data quality and consistency by implementing validation, monitoring, and documentation standards; establish strong data governance practices across marketing and growth analytics
Help instill a data-first culture by making tools and metrics intuitive, reliable, and accessible. Provide guidance to teammates on how to use and interpret data
Continuously enhance data infrastructure by optimizing systems, evaluating new tools, and promoting data best practices across the organization
Work closely with cross-functional teams to understand data requirements and deliver solutions that meet business needs
REQUIREMENTS:
Bachelor’s or Master’s degree in quantitative fields (Computer Science, Statistics, Economics) or a related field
4+ years of experience in data science, analytics, product analyst or a similar discipline
2+ years of experience working with blockchain or order book data (e.g. experience indexing blocks, building dashboards in Dune or similar, working with market data from crypto exchanges)
Expertise in SQL, database technologies, cloud databases, and reporting technologies (BigQuery, GCP, and Mode or similar)
Proficient in Python,
Proficient with data visualization tools for generating insights and communicating findings effectively
Solid understanding of ETL processes, data modeling, and data warehousing principles
Entrepreneurial and intellectually curious, with a passion for asking the right questions, exploring data, and developing well-reasoned hypotheses
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