Title: Senior Business Analyst – Data Science & Market Analytics
Location : DC Metro Area, NYC Metro Area
Target Start Date : ASAP
Type: contract
Pay Rate: DOE
We are seeking a highly analytical Senior Business Analyst to bridge the gap between business stakeholders, data science, and technology teams in a complex, data-driven environment. This individual will play a critical role in transforming business challenges into scalable analytical solutions through data exploration, rapid prototyping, experimentation, and production implementation.
The ideal candidate combines strong business analysis skills with hands-on data science capabilities, experience working with financial or market-related data, and the ability to communicate complex technical concepts to non-technical audiences. This role requires someone who can independently investigate large datasets, identify patterns and opportunities, build proof-of-concept solutions, and partner with engineering teams to operationalize solutions in production environments.
Key Responsibilities
- Partner with business stakeholders to understand complex business problems, requirements, and objectives.
- Analyze large and complex datasets to identify trends, anomalies, opportunities, and actionable insights.
- Leverage data science methodologies, statistical analysis, and machine learning techniques to solve business challenges.
- Design and develop prototypes and proof-of-concept solutions to validate ideas and rapidly test hypotheses.
- Apply an iterative "experiment, learn, and refine " approach to solution development.
- Translate business requirements into functional specifications and work closely with engineering teams to deliver production-ready solutions.
- Support user acceptance testing (UAT), implementation, and ongoing enhancement of analytical solutions.
- Investigate data discrepancies, validate outputs, and ensure data accuracy and completeness.
- Interpret complex business logic, data processing workflows, and source code to understand system behavior and data lineage.
- Create clear business-facing documentation, including business requirements, solution designs, operational procedures, and knowledge articles.
- Develop visualizations and presentations that effectively communicate findings and recommendations to technical and non-technical audiences.
- Serve as a subject matter expert on business processes, data structures, and analytical methodologies.
Required Qualifications
- Bachelor's degree and 5+ years of relevant experience, or an advanced degree with 2+ years of relevant experience.
- Strong experience working with complex datasets and applying data-driven problem-solving techniques.
- Proficiency in data mining, statistical analysis, and quantitative reasoning.
- Strong SQL skills, including analysis of large-scale datasets on distributed platforms.
- Proficiency in Python or another scripting/programming language for data analysis, automation, and prototyping.
- Experience applying machine learning algorithms and analytical techniques to solve business problems.
- Demonstrated ability to build prototypes, conduct experiments, and iterate toward scalable solutions.
- Experience working with financial markets, market data, trading environments, banking, capital markets, or similarly complex data domains.
- Strong analytical and investigative skills with the ability to independently validate results and troubleshoot data issues.
- Ability to read and interpret source code, data pipelines, and complex business logic.
- Advanced spreadsheet and data analysis skills.
- Strong data visualization and storytelling capabilities.
- Excellent written and verbal communication skills, including the ability to translate highly technical concepts into business-friendly language.
- Experience collaborating with software engineering teams to move solutions from prototype to production.
Preferred Qualifications
- Degree in Finance, Business Administration, Computer Science, Data Science, Statistics, Mathematics, or a related field; advanced degree preferred.
- Understanding of financial markets, securities, equities, options, market structure, or regulatory environments.
- Experience supporting analytical platforms, surveillance systems, risk systems, trading systems, or other data-intensive business applications.
- Experience with distributed query engines, big data technologies, and cloud-based analytics platforms.
- Experience using Generative AI tools, LLMs, and AI-assisted development platforms to accelerate analysis, prototyping, documentation, and code comprehension.
- Familiarity with source code management, version control, and release management workflows.
- Experience partnering across business, product, engineering, and data science organizations.
Success Profile
The successful candidate is naturally curious, thrives in ambiguity, enjoys exploring data to uncover insights, and is comfortable challenging assumptions through experimentation and evidence-based analysis. They can move seamlessly between business discussions, technical investigations, prototype development, and production implementation while maintaining a strong focus on delivering measurable business value.
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