Business Intelligence Analyst

Job Title: Business Intelligence AnalystLocation: Stamford, CT - 3 Days on - SiteDepartment: Intelligence & Surveillance / Data & AnalyticsAbout The TeamOur 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.Role OverviewAs 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.Key Responsibilities (Detailed)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. Required Qualifications 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, NumPy, 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. Preferred Tech Stack (Hands-on with at least several)CategoryTechnologies / ToolsDatabases & QueryingSQL (PostgreSQL, MySQL, Snowflake, BigQuery), NoSQL (Elasticsearch, MongoDB)Programming & AnalyticsPython (Pandas, NumPy, Scikit-learn, Hugging Face, LangChain), Jupyter, GitBI & VisualizationTableau, Power BI, Looker, or SupersetAI / LLM ToolingOpenAI API, Anthropic API, LangChain, LlamaIndex, vector databases (Pinecone, Weaviate, FAISS), basic RAG patternsWorkflow & AutomationApache Airflow, Prefect, or similar orchestration tools; basic API integration (REST)Documentation & ComplianceMarkdown, Jupyter notebooks, data catalog tools (e.g., DataHub, Amundsen)Cloud & Data Platforms (nice to have)AWS (S3, Lambda, Redshift), GCP, Azure, Databricks, or SnowflakeWhat We Offer (Standard Benefits)Fully-paid health care benefits (medical, dental, vision) Generous parental and family leave policies Mental and physical wellness programs Volunteer opportunities & non-profit matching gift program Support for employee-led affinity groups Tuition assistance and continuous learning budget 401(k) savings program with employer match Skills: design,business intelligence,python,data,power bi,intelligence,databases,analytics