Data Scientist

DyDx Exchange•New York, NY

42d•$190,000 - $240,000

About The Position

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 NICE TO HAVES: Familiarity with cloud data platforms (e.g., AWS, GCP, Azure) Understanding of machine learning and data science methodologies Experience or knowledge in trading, particularly high-frequency trading (HFT), market structure, and derivatives Passion for DeFi and web3, with specific interest in dYdX and a proven track record Relevant certifications in data engineering or analytics Salary range for this job is $190K to $240K USD (NY). Compensation subject to experience and location. Published salary bands pursuant to transparency laws, and do not include possible variable compensation such as annual merit increases, bonus eligibility, commission, or equity incentive.

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

Nice To Haves

Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)
Understanding of machine learning and data science methodologies
Experience or knowledge in trading, particularly high-frequency trading (HFT), market structure, and derivatives
Passion for DeFi and web3, with specific interest in dYdX and a proven track record
Relevant certifications in data engineering or analytics

Responsibilities

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
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