Applied Data Scientist

Overview

Job Description

Responsibilities

• - Collaborate with the Smart Signals Product team to improve fraud detection signals, including browser bot detection, VM detection, VPN detection, and more
• - Conduct deep dives into problematic features, researching and analyzing their behavior to understand root causes and identify potential solutions
• - Develop hypotheses, run experiments, analyze results, and translate findings into actionable engineering improvements
• - Build and enhance backend systems for real-time data processing and model inference
• - Develop scalable web services that integrate machine learning models to analyze large datasets and extract insights
• - Drive the integration of machine learning solutions into production systems, ensuring performance, scalability, and reliability
• - Foster a data-driven culture by sharing engineering best practices and collaborating on cross-functional projects

Required Skills

• - Proficient in English for clear communication in a global, remote team
• - BS/MS in Computer Science, Data Science, or a related field, or equivalent work experience
• - 3+ years of experience in backend development with exposure to data science and machine learning
• - Strong experience in designing, developing, and maintaining scalable backend systems
• - Experience working with real-time data processing, APIs, and integrating machine learning models into production services
• - Excellent coding skills, particularly in GoLang (or equivalent), with working knowledge of data engineering practices
• - Familiarity with supervised and unsupervised learning methods
• - Experience working with machine learning pipelines, model deployment, and performance monitoring
• - Understanding of core ML concepts such as feature engineering, model evaluation, and real-time inference
• - Strong knowledge of SQL and experience with databases like DynamoDB, Redis, or Elasticsearch
• - Proficiency with general software engineering tools: Git, IDEs, shell scripting, CI/CD
• Nice to Have:
• - Practical experience with analytical storage systems like ClickHouse, Snowflake, BigQuery, Redshift, or Databricks
• - Experience with data transformation frameworks like dbt or other data pipeline tools
• - Familiarity with data visualization tools such as Apache Superset, Tableau, or Looker
• - Experience with the Python data analytics stack (Numpy, Pandas, Jupyter, etc.)

Benefits

• - Compensation range: $130,000 - $190,000
• - We set standard ranges for all US-based roles based on function, level, and geographic location, benchmarked against similar-stage growth companies.
• - Inclusive and remote work environment
• - We embrace and celebrate the unique experiences, perspectives, and cultural backgrounds that each employee brings to our workplace
• - We highly encourage people from underrepresented groups in tech to apply