Senior Data Scientist

About Us

Alpaca is a US-headquartered self-clearing broker-dealer and brokerage infrastructure for stocks, ETFs, options, crypto, fixed income, and 24/5 trading. Our recent Series C funding round brought our total investment to over $170 million. We serve hundreds of financial institutions across 40 countries with institutional-grade APIs, including broker-dealers, investment advisors, wealth managers, hedge funds, and crypto exchanges.

The Role

We are seeking an experienced Senior Data Scientist to join our remote, distributed team. This role is pivotal in driving insights and innovation from our rich data ecosystem, including financial transactions, customer data, API usage patterns, and third-party sources.

Responsibilities

• Lead Advanced Analysis: Design and execute deep predictive and descriptive analyses across core business domains, including finance, marketing, and product metrics
• Develop Agentic AI: Spearhead research, proof-of-concept (PoC), and full-lifecycle development of data-intensive applications with a focus on agentic AI systems
• Drive Model Lifecycle: Own end-to-end development of data science solutions from initial research through deployment, optimization, and maintenance
• Cross-Functional Collaboration: Work closely with stakeholders in sales, marketing, product, and operations to translate complex business needs into actionable, data-driven solutions
• Evolve Capabilities: Contribute to Alpaca's data science capabilities by championing best practices in statistical modeling, MLOps, and advanced AI

Requirements

• Domain Experience: Proven experience as a Senior Data Scientist with direct, hands-on experience in brokerage, trading, or financial services industry
• Technical Proficiency: Expert-level proficiency in Python (including data science libraries like pandas, scikit-learn) and advanced SQL
• Data Science Expertise: Deep understanding of statistical methods for supervised and unsupervised learning, with a strong portfolio of building and deploying models in production environments
• Cloud & Data Warehousing: Hands-on experience with cloud-native data warehouses (Snowflake, BigQuery, Redshift; we use Trino & Iceberg) and modern ETL processes
• Full-Stack Mindset: Ability to lead projects through entire lifecycle and strong understanding of handling high-volume data
• Collaboration: Excellent communication skills and proven ability to thrive in fast-paced, collaborative environments

Preferred Qualifications

• Agentic AI / LLMs: Direct experience building applications using Large Language Models or agentic AI frameworks (we use Google Agent Engine)
• Semantic Layers: Familiarity with data modeling and semantic layers (e.g., dbt Semantic Layer, Cube.js, LookML)

Benefits

• Competitive Salary & Stock Options
• Health Benefits
• New Hire Home-Office Setup: One-time USD $500
• Monthly Stipend: USD $150 per month via Brex Card