Data Scientist - DyDx

De Circle

$100K — $150K *
New York, NY 10025Remote in New York, NY
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in quantitative fields such as Computer Science, Statistics, or Economics.
  • 4+ years of experience in data science, analytics, product analysis, or a related field.
  • 2+ years of experience with blockchain or order book data, particularly from crypto exchanges.
  • Expertise in SQL and data technologies, particularly in cloud databases like BigQuery and GCP.
  • Proficient in Python and data visualization tools to communicate insights effectively.

Responsibilities

  • Collaborate with marketing and cross-functional teams to translate data insights into actionable strategies.
  • Analyze growth funnels and campaign performance to enhance acquisition and retention efforts.
  • Own the attribution analysis across various marketing channels to refine user acquisition tactics.
  • Design and conduct A/B tests aimed at boosting user conversion rates.
  • Maintain scalable data pipelines to facilitate self-serve analytics and robust marketing dashboards.
  • Ensure data quality and consistency through validation processes and strong governance practices.
  • Promote a data-driven culture by making analytics tools intuitive for the team.

Benefits

  • Opportunity to work on cutting-edge decentralized technologies in finance.
  • Chance to influence the strategy and decisions of a growing company.
  • Engagement with a collaborative team environment across various functions.
Full Job Description
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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