Alpaca - Senior Data Scientist
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Requirements
• Domain Experience: Proven experience as a Senior Data Scientist with direct, hands-on experience in the brokerage, trading, or financial services industry. • brokerage, trading, or financial services industry • Technical Proficiency: Expert-level proficiency in Python (including common data science libraries like pandas, scikit-learn, etc.) and advanced SQL. • Technical Proficiency: • Python • 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 a production environment. • Data Science Expertise: • Cloud & Data Warehousing: Hands-on experience with cloud-native data warehouses (e.g., Snowflake, BigQuery, Redshift; we use Trino & Iceberg) and familiarity with modern ETL processes. • Cloud & Data Warehousing: • cloud-native data warehouses • Full-Stack Mindset: Ability to lead projects through the entire lifecycle (research, development, deployment, maintenance) and a strong understanding of handling high-volume data. • Full-Stack Mindset: • Collaboration: Excellent communication skills and a proven ability to thrive in a fast-paced, collaborative environment, translating complex findings for non-technical stakeholders. • Collaboration: • Agentic AI / LLMs: Direct experience building applications using Large Language Models (LLMs) or agentic AI frameworks (we use Google Agent Engine). • Agentic AI / LLMs: • Semantic Layers: Familiarity with data modelling and semantic layers (e.g., dbt Semantic Layer, Cube.js, LookML). • Semantic Layers: • How We Take Care of You: • Competitive Salary & Stock Options • Health Benefits • New Hire Home-Office Setup: One-time USD $500 • Monthly Stipend: USD $150 per month via a Brex Card • Alpaca is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce. • Recruitment Privacy Policy
Responsibilities
• You will be responsible for applying deep predictive and descriptive analytics to unlock strategic value and will be a key player in developing our next generation of agentic AI applications. • Lead Advanced Analysis: Design and execute deep predictive and descriptive analyses across our core business domains, including finance, marketing, and product metrics, to identify key trends, optimization opportunities, and strategic insights. • Lead Advanced Analysis: • finance, marketing, and product metrics • Develop Agentic AI: Spearhead the research, proof-of-concept (PoC), and full-lifecycle development of data-intensive applications, with a specific focus on building and deploying agentic AI systems. • Develop Agentic AI: • building and deploying agentic AI systems • Drive Model Lifecycle: Own the end-to-end development of data science solutions, from initial research and data handling (high-volume transactions, metrics) through to deployment, optimization, and maintenance. • Drive Model Lifecycle: • Cross-Functional Collaboration: Work closely with stakeholders in sales, marketing, product, and operations to understand complex business needs and translate them into actionable, data-driven solutions. • Cross-Functional Collaboration: • Evolve Capabilities: Contribute to the evolution of Alpaca's data science capabilities by championing best practices in statistical modelling, MLOps, and advanced AI. • Evolve Capabilities:
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