Senior Data Scientist, Fraud Strategy

New York City; Seattle, Washington; San Francisco, California

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Gemini

Gemini makes crypto simple. Find, Trade and Buy over 80 coins including bitcoin on the best cryptocurrency platform. Start trading crypto here.

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Empower the Individual Through Crypto

Gemini is a crypto exchange and custodian that allows customers to buy, sell, store, and earn more than 30 cryptocurrencies like bitcoin, bitcoin cash, ether, litecoin, and Zcash. Gemini is a New York trust company that is subject to the capital reserve requirements, cybersecurity requirements, and banking compliance standards set forth by the New York State Department of Financial Services and the New York Banking Law. Gemini was founded in 2014 by twin brothers Cameron and Tyler Winklevoss to empower the individual through crypto.

Crypto is about giving you greater choice, independence, and opportunity. We are here to help you on your journey. We build crypto products that are simple, elegant, and secure. Whether you are an individual or an institution, we want to help you buy, sell, and store your bitcoin and cryptocurrency. Crypto is not just a technology, it's a movement.

At Gemini, our mission is to empower the individual and that includes giving our employees flexibility of choice — our Office Optional Policy allows employees to choose to work from one of our physical locations or from home.

The Department: Trust & Safety

Trust & Safety at Gemini is a team dedicated to stopping bad actors, securing our user’s funds and ensuring the integrity of Gemini’s digital asset marketplace. We are a diverse group of technology, legal, and operational professionals who develop new approaches to solving classic problems using cutting edge tools and processes.

The Role: Senior Data Scientist, Fraud Strategy

Gemini’s Trust & Safety team is looking for a Senior Data Scientist, Fraud Strategy to contribute to Gemini’s efforts to create the most trusted crypto exchange and crypto-reward Credit Card product in the market. In this role, you will be the leader of the Gemini Exchange & Credit Card Fraud vertical, and responsible for proactively identifying, investigating, responding to and ultimately preventing exchange and credit card fraud, while ensuring our customers have a both secure and seamless experience. You will focus on customer onboarding, transactions, and payment strategies to lower payment return rates, unauthorized transaction rates, and identify and off-board bad actors from Gemini, as well as manage ad-hoc requests from cross-functional teams. You will play a major part in building and setting the direction of a high-performing team.

Responsibilities:

  • Lead the data science team that sets the fraud loss strategy and conducts proactive monitoring and investigations focusing on our retail exchange and credit card product, through analysis of disparate sources of data (application and transaction activity, internal models, server logs, customer support tickets, etc.)
  • Formulate, implement, and document investigative rules and policies that help the company effectively fight fraud
  • Extrapolate lessons learned from investigations and inform upgrades to the fraud detection rules and operational guidelines to help the company more efficiently fight credit card fraud
  • Collaborate with Customer Support, Product, Credit, Compliance, Engineering and Security on improving processes to prevent and respond to fraud
  • Take ownership of projects and make decisions in a fast-paced environment with minimal direction

Minimum Qualifications:

  • 5+ years experience in data analytics, strategy analytics or modeling role
  • 3+ years of people management experience in leading a data science or analytics team
  • 5+ years experience developing a BI applications (Tableau/Looker/Power BI, etc)
  • Advanced skills with SQL are a must
  • Proficient in Python
  • Experience with one or more MPP databases (Redshift, Bigquery, Snowflake, etc)
  • Experience with one or more ETL tools (Informatica, Pentaho, SSIS, etc)
  • Experienced in payment and or credit card fraud
  • Experienced in working collaboratively across different teams and departments
  • Strong technical and business communication
  • This role may require on-call rotations

Preferred Qualifications:

  • Experience in working at both Financial Lending Issuer side and E-commerce/Brokerage merchant side fraud issues
  • Experience in working with cards and ACH payment processing
It Pays to Work Here   The compensation & benefits package for this role includes:
  • Competitive starting salary
  • A discretionary annual bonus
  • Long-term incentive in the form of a new hire equity grant
  • Comprehensive health plans
  • 401K with company matching
  • Annual Learning & Development stipend
  • Paid Parental Leave
  • Flexible time off

Salary Range: The base salary range for this role is between $136,000 - $190,000 in New York City, the State of California and the State of Washington. This range is not inclusive of our discretionary bonus or equity package. When determining a candidate’s compensation, we consider a number of factors including skillset, experience, job scope, and current market data.

At Gemini, we strive to build diverse teams that reflect the people we want to empower through our products, and we are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Gemini is proud to be an equal opportunity workplace. If you have a specific need that requires accommodation, please let a member of the People Team know.

Tags: Banking BigQuery Crypto Data Analytics E-commerce Engineering ETL Gemini Informatica Looker MPP Pentaho Power BI Python Redshift Security Snowflake SQL SSIS Tableau

Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Health care Home office stipend Parental leave Salary bonus Team events

Region: North America
Country: United States
Job stats:  20  5  0
Category: Data Science Jobs

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