Senior Machine Learning Engineer, Trust & Safety

Key Skills

AWS Sagemaker, Data Analytics, Data science techniques, Databricks, Machine learning techniques, MLflow, Natural Language Processing (NLP), Snowflake

Job Description

The Role:

Senior Machine Learning Engineer

As a member of our Trust and Safety data science team, you’ll shape the way we approach data at Gemini by using your analytical and communication skills to work with teams across the business. You will focus on transactions, account takeovers, scams, and payment strategies to lower payment return rates and identify and off-board bad actors from Gemini, as well as manage ad-hoc requests from cross-functional teams. You know how to ask the right questions and are passionate about using machine learning to support and drive informed business decisions. You are ready to roll up your sleeves and are excited to take on challenging opportunities and projects. You’ll work with other data scientists, analysts, engineers, and fraud operators to guide strategies, build machine learning models, and achieve KPIs while communicating your insights with leaders across the organization.

This role is required to be in person twice a week at either our Seattle, WA, New York City, NY, or Miami, FL office.

Responsibilities:

• Design and develop Trust & Safety machine learning and AI models to optimize across fraud, crypto exchange trading, and anti money laundering.
• Distill complex models and analysis into compelling insights for our stakeholders and executives.
• Analyze large and complex datasets to identify patterns for feature engineering, trends, and anomalies and develop predictive models that can be used for decision-making.
• Collaborate with software developers to design and implement machine learning systems that can improve the speed and accuracy of the machine learning models.
• Monitor and analyze the performance of our machine learning models and systems and make necessary improvements to ensure their effectiveness.
• Stay up-to-date with data science tools and methodologies in technology and financial domain.
• Perform root cause analysis and resolve production and data issues.

Minimum Qualifications:

• Bachelor's degree in computer science, data science, mathematics, or a related field.
• 4+ years of work experience in analytics and data science domain focusing on financial services-related business problems.
• 3+ years of experience deploying statistical and machine learning models in production.
• 2+ years of experience in integrating data science models into applications.
• Proven experience in developing and deploying ML models at scale, with a deep understanding of model lifecycle management.
• Knowledge and experience of crypto exchange trading, financial markets, or banking.
• Extensive knowledge of ML lifecycle management tools (Sagemaker, ML Flow, or similar ones), libraries, data structures, data modeling, and software architecture.
• Advanced skills with SQL are a must.
• Proficient in Python.
• Experience with one or more big data tools and technologies like Snowflake, Databricks, S3, Hadoop, Spark.
• Experienced in working collaboratively across different teams and departments.
• Strong technical and business communication.

Preferred Qualifications:

• Master’s degree in computational linguistics, data science, data analytics, or similar Proficient in Developing LookML.
• Experience working with NLP applications is a plus.
• Experience working in small firms, financial technology, or start up technology.

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
• Paid Parental Leave
• Flexible time off

Salary Range: The base salary range for this role is between $140,000 - $200,000 in the State of New York, 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.

In the United States, we have a flexible hybrid work policy for employees who live within 30 miles of our office headquartered in New York City and our offices in Seattle and Miami. Employees within the New York, Seattle, and Miami metropolitan areas are expected to work from the designated office twice a week, unless there is a job-specific requirement to be in the office every workday. Employees outside of these areas are considered part of our remote-first workforce. We believe our hybrid approach for those near our NYC, Seattle, and Miami offices increases productivity through more in-person collaboration where possible.

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.