Business Intelligence Analyst

Business Intelligence Analyst

Location: Stamford, CT - 3 Days on‑Site

Department: Intelligence & Surveillance / Data & Analytics

Our Intelligence and Surveillance team sets the industry standard for intelligence‑driven analysis. We proactively identify, monitor, and assess various sources of risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real‑time escalations.

As a Business Intelligence Analyst, you will help design, build, and deploy intelligent workflows that transform multimodal data (structured, semi‑structured, and unstructured) into verifiable, transparent, and compliant insights. You will blend strong analytical thinking with practical AI application, grounded in rigor, accountability, and measurable business impact.

• Stakeholder Partnership & Requirements Gathering:
  Collaborate directly with business stakeholders (e.g., compliance, operations, legal, trading desks) to identify operational inefficiencies and design AI‑driven automations that meaningfully improve day‑to‑day workflows.
• AI & Workflow Design:
  Architect and implement intelligent automations using a combination of traditional business intelligence (BI) methods and modern large language models (LLMs). Translate complex business problems into technical solutions with clear success metrics.
• Data Transformation & Integration:
  Extract, clean, and integrate data from multiple internal and external sources (databases, APIs, logs, document repositories). Build reusable data pipelines that feed both analytical dashboards and automated decision systems.
• Compliance & Auditability:
  Maintain thorough documentation of data lineage, testing protocols, and audit trails. Ensure all outputs (reports, models, alerts) are verifiable, reproducible, and meet firm‑wide accuracy and regulatory compliance standards.
• Communication & Translation:
  Serve as a knowledgeable bridge between business teams and engineering/product partners. Help non‑technical stakeholders understand AI capabilities, limitations, and value propositions. Present findings and recommendations to senior management.
• Continuous Innovation:
  Monitor emerging AI tools, agentic frameworks, and prompt engineering techniques. Proactively identify practical opportunities for adoption to improve speed, quality, and efficiency across the organization.
• Quality Assurance & Data Integrity:
  Diagnose and resolve data quality issues, including inconsistencies, missing values, and anomalies. Implement automated validation checks and monitoring.

• Education:
  
  Master’s degree in Data Science, Decision Science, Industrial/Organizational (I/O) Psychology, Computer Science, or a related quantitative field.
• Experience:
  
  4+ years in a data analyst, business analyst, technical product, or BI engineering role.
• Core Technical Proficiency:
  • SQL:
    Expert‑level proficiency in writing, debugging, and optimizing complex queries (joins, window functions, CTEs, query performance tuning) across relational databases (e.g., PostgreSQL, MySQL, or Snowflake).
  • Python:
    Experience using Python for data profiling, cleaning, and analysis, including libraries such as Pandas, Num Py, and Jupyter notebooks.
  • AI/LLM Platforms:
    Hands‑on experience applying foundation models (e.g., GPT‑4, Claude, Llama) to real business problems, including prompt engineering, chain‑of‑thought reasoning, retrieval‑augmented generation (RAG), and working with LLM APIs (OpenAI, Anthropic, or similar).
• Analytical & Problem Solving:
  Strong analytical foundations (statistics, hypothesis testing, data visualization principles). Proven ability to identify, diagnose, and resolve data quality and integrity issues.
• Soft Skills:
  
  Ability to explain AI‑driven concepts to both technical and non‑technical audiences. Demonstrated bias toward action, intellectual curiosity, and disciplined execution in fast‑paced, evolving environments.
• Ethics & Integrity:
  Commitment to the highest ethical standards, particularly regarding data privacy, compliance, and responsible AI use.

• Databases & Querying: SQ…