Sr. AI, Data Science, Quant Developer Analyst

Our Client: Global Investment Bank is seeking :

Sr. AI, Data Science, Quant Developer Analyst

Location: Midtown, New York, NY

for Onsite: 4 days onsite / 1 day remote work schedule

Level: Senior

""" must be local to New York Metro area and have Invetment Management experience"""

Job Description

Our Client: Global Investment Bank is seeking a Client Facing

Data Science & Analytics - AI Developer to lead analytical and AI work in client-facing engagements and internal strategic initiatives.

Seeking strong quantitative professional who can manage stakeholder cycles, shape problem statements, and drive workstreams from scoping through delivery.

With focus on client-facing work, while also contributing to the firm’s internal AI and analytics building; combine quantitative rigor with commercial judgment and strong stakeholder management

Firm is building a more mature data science and AI capability to support client delivery, differentiated insight generation, and scalable internal tools.

Responsibilities:

will play a key role in translating business questions into analytical solutions, leading execution against those solutions, and ensuring outputs are practical, defensible, and decision useful.

As a Data Science & Analytics, you will work bankers, senior business stakeholders, data science, engineering, and business analysis teams.

Operate independently, manage multiple workstreams, and help set the standard for how analytical products are scoped, built, communicated, and scaled.

Lead analytical workstreams tied to client-facing opportunities and strategic internal priorities

• Translate business needs into structured analyses, models, and workflows
• Manage stakeholder engagement, delivery cadence, and quality control across project cycles
• Help convert bespoke analytical work into repeatable internal capabilities where appropriate
• Lead analytical workstreams that support client engagements, strategic analyses, sector intelligence, and banker decision-making
• Partner with bankers and senior stakeholders to define analytical objectives, scope work, prioritize use cases, and align on delivery plans
• Translate business problems into data requirements, methodological approaches, and actionable workstreams
• Present findings, tradeoffs, recommendations, and implications clearly to both technical and non-technical audiences
• Help ensure analytical outputs are client-ready, commercially relevant, and grounded in sound methodology

Quantitative

• Design and oversee statistical, machine learning ( ML ), NLP, forecasting, optimization, and other analytical approaches suited to the business problem
• Remain hands-on where needed in data extraction, data preparation, model development, testing, and interpretation
• Review work produced by junior team members for technical rigor, logic, clarity, and usability
• Build and improve analytical frameworks, reusable code assets, and scalable processes that raise team efficiency and quality
• Partner with engineering and adjacent teams to support deployment or operationalization of analytical solutions where appropriate

AI

• Contribute to the firm’s internal AI and analytics platform by helping identify reusable patterns from client-facing work
• Shape AI-enabled workflows and use cases tied to insight generation, knowledge retrieval, summarization, classification, and productivity
• Collaborate with AI, product, and technology teams to move from proof-of-concept to production-aligned solutions
• Help define where machine learning, statistical modeling, and LLM-based approaches are most appropriate and where they are not

• Own end-to-end workstream management across discovery, analysis, validation, communication, and follow-through
• Set clear project cadences, milestones, dependencies, and decision points for stakeholders
• Support sound practices around documentation, testing, model transparency, data lineage, controls, and issue management
• Help define KPIs and success metrics for analytics and AI use cases, including business impact, adoption, efficiency gains, and model quality
• Ensure deliverables meet internal quality, compliance, and governance expectations

• Mentor Analysts and junior team members, helping improve technical quality, business framing, and communication
• Foster strong partnership across bankers, business analysts, engineers, and business stakeholders
• Contribute to operating discipline, prioritization, and best practices across the broader analytics and AI function
• Help build a culture that values rigor, practicality, speed, and measurable business impact

Education

• Bachelor’s degree: (Data Science, Statistics, Mathematics, CS, Engineering, Economics, Finance, or a related quantitative field

Experience

• 5 – 8 years of experience in data science, analytics, quantitative consulting, financial services
• Experience in investment banking, capital markets, financial services, consulting, or other high-performance client environments
• experience managing analytical projects or workstreams from problem framing through delivery
• Experience engaging directly with senior stakeholders or clients
• Strong quantitative and analytical problem-solving capabilities
• Ability to structure ambiguous business questions into clear analytical plans and executable workstreams
• Strong communication and stakeholder management skills, including the ability to influence across senior audiences
• Ability to balance technical rigor with commercial relevance and delivery practicality
• Strong organization and prioritization skills across concurrent projects

AI, Data, and Technical Skills

• Strong experience with Python and SQL required
• Strong grounding in statistics, machine learning, experimentation, data interpretation, and model evaluation
• Experience working with structured and unstructured data at scale
• Familiarity with modern AI tooling, LLMs, prompt engineering, retrieval-based workflows, and applied AI use cases
• Experience with data visualization and storytelling tools such as Power BI or Tableau preferred
• Familiarity with software delivery concepts, version control, and production-oriented analytical development practices preferred
• Exposure to cloud, data engineering, or model deployment workflows is a plus

we are seeking:

• Commercially minded and execution-oriented
• Comfortable leading workstreams in a fast-paced, high-accountability environment
• Strong judgment, maturity, and client-service orientation
• Able to coach junior talent while remaining hands-on when needed