Quantitative Research Analyst focusing on equity market microstructure and systematic investment strategies.
Responsibilities
Analyse equity trading dynamics, liquidity, price formation, order flows and market impact using large-scale market and transaction datasets
Research and develop predictive indicators and systematic investment strategies combining market microstructure, trading activity and stock characteristics
Apply advanced statistical methods, machine learning and data science techniques to identify patterns and extract actionable signals from financial data
Design robust backtesting frameworks, assess predictive power and strategy performance across different market environments
Contribute to the development, automation and monitoring of quantitative indicators ensuring data quality, computational efficiency and reliability
Requirements
Master's degree or engineering degree from a leading university or Grande École, specialising in Applied Mathematics, Statistics, Data Science, Quantitative Finance or a related field
Design, develop, and maintain automated test frameworks for backend services, APIs, and document processing pipelines to ensure high data quality and release confidence.
Responsibilities
Design and develop automated test frameworks for backend services, APIs, and document processing pipelines.
Build automated validation for HTML, XML, JSON, PDF, and structured/unstructured data.
Implement data quality checks, schema validation, metadata validation, and content integrity verification.
Develop API, integration, regression, and end-to-end automated test suites.
Build continuous quality feedback loops integrated with CI/CD pipelines.
Hands-on individual contributor supporting the North America Marketing Automation team. This role builds, tests, and deploys email campaigns in Salesforce Marketing Cloud (SFMC) and provides steady-state coverage of the team's weekly send calendar.
Compensation
$50.00 - $55.07/hr. on W2.
Responsibilities
Build and deploy email campaigns in SFMC end to end: audience setup, targeting, QA, and deployment.
Write SQL queries across data extensions to build, segment, and validate audiences.
Build, monitor, and troubleshoot journeys in Journey Builder and automations in Automation Studio.
Manage the daily email send calendar and keep campaigns on schedule.
Partner with the development team, who deliver email code and templates, to assemble and launch dynamic and personalized content.
Requirements
Nice to have: Salesforce Marketing Cloud Email Specialist certification
Contributes to the overall success of GFT and Finance Data Platform (FRDP) by designing, building, and owning scalable and reliable data pipelines.
Compensation
We offer a competitive total rewards package, including a performance bonus, company matching programs (on pension & profit sharing), and generous vacation
Responsibilities
Design, develop, and own ingestion, transformation, and publishing pipelines across FRDP
Build scalable data workflows across structured, semi-structured, and unstructured datasets
Design data models aligned with business and analytical requirements
Develop transformation logic using SQL and distributed processing frameworks such as Spark
Implement and enforce data quality frameworks and validation rules
Senior engineering leader responsible for translating business opportunities into secure, scalable AI solutions and leading cross‑functional delivery pods.
Responsibilities
Develop and manage AI solution roadmap
Partner with business and technology leaders to prioritize high‑value opportunities
Translate business objectives into delivery plans
Lead cross‑functional delivery pods
Own delivery outcomes for assigned solutions
Requirements
Bachelor’s or master’s degree in computer science, software engineering, data science, information systems, or a related field
Own the data layer that makes production legible, ingesting from ShotGrid, Dynamics 365, and other systems, building semantic models, and delivering dashboards and insights to production, finance and leadership.
Design, develop, validate, and deploy predictive ML models and GenAI solutions for formulation and product development in cosmetics and scientific domain.
Compensation
Pay: $50-54.43/hour W2 only
Responsibilities
Design, develop, validate, and deploy predictive ML models, including regression, classification, clustering, and time-series forecasting.
Develop GenAI solutions using Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and AI frameworks.
Select appropriate ML or GenAI approaches based on model performance, cost, and business value.
Evaluate and monitor production models for performance, data drift, hallucinations, bias, and cost.
Perform data exploration, cleaning, and analysis across structured and unstructured datasets.
Requirements
Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related STEM field
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