We are looking for a Data Scientist to join a fast-paced investment environment in New York, New York, where data-driven insight plays a central role in research and decision-making. This position will focus on turning complex datasets into practical analysis, scalable tools, and clear intelligence that support investment ideas. The ideal candidate brings strong technical depth, sound statistical judgment, and the ability to shape loosely defined questions into structured, repeatable research.<br><br>Responsibilities:<br>• Work closely with investment professionals to create quantitative studies, analytical frameworks, and practical tools that strengthen fundamental research workflows.<br>• Identify promising alternative data sources, assess their relevance and quality, and support their integration into the research process.<br>• Design and execute backtests, predictive models, and exploratory investigations to evaluate and refine investment hypotheses.<br>• Produce and maintain analyst-facing dashboards and reporting views within internal analytics environments.<br>• Convert one-off research requests into repeatable, clearly documented analyses that can be reused and scaled over time.<br>• Partner with engineering teams to define data needs, support ingestion processes, and improve dataset availability for research use.
We are looking for a Data Analyst to join a team in Somerset, New Jersey and turn complex information into actionable insight that strengthens fraud detection efforts. This contract opportunity with potential for a permanent role is ideal for someone who combines strong analytical thinking with practical experience identifying suspicious patterns, supporting investigations, and improving anti-fraud decision-making. The role offers the chance to work closely with business partners to interpret data, surface risk trends, and contribute to a more proactive fraud strategy.<br><br>Responsibilities:<br>• Examine large data sets to identify unusual activity, emerging fraud patterns, and indicators of potential risk.<br>• Create reports, dashboards, and analytical summaries that help stakeholders monitor fraud performance and make informed decisions.<br>• Partner with investigation and business teams to translate data findings into practical actions that support fraud prevention efforts.<br>• Evaluate transactional and behavioral information to uncover trends, root causes, and opportunities to reduce exposure.<br>• Support fraud investigations by gathering, organizing, and interpreting relevant data from multiple sources.<br>• Refine analytical methods and detection approaches to improve accuracy, efficiency, and responsiveness in anti-fraud initiatives.
We are looking for a Data Analyst to support reporting, visualization, and data-driven decision-making for a long-term contract opportunity in Brooklyn, New York. This position is ideal for someone who can translate complex information into clear insights while partnering with both business stakeholders and technical teams. The role will focus on analytics, reporting development, and data interpretation within an energy and natural resources environment, with opportunities to contribute to broader data integration and advanced analytics efforts.<br><br>Responsibilities:<br>• Build and maintain dashboards, reports, and visualizations that turn large datasets into meaningful business insights.<br>• Analyze operational and financial information to identify trends, exceptions, and performance patterns that support decision-making.<br>• Partner with cross-functional teams to gather reporting needs and convert business questions into effective analytical solutions.<br>• Work with structured data sources and databases to validate accuracy, improve accessibility, and support ongoing reporting processes.<br>• Contribute to data integration and architecture-related initiatives by helping connect information across systems and business functions.<br>• Support reporting tied to finance and accounting activities, including datasets related to general ledger processes.<br>• Use tools such as Power BI or Tableau to present findings in a clear, actionable format for stakeholders.<br>• Assist with exploratory analytics and emerging initiatives involving Python, AI-enabled analysis, or machine learning concepts when applicable.
Job Responsibilities Design, build, and maintain scalable ERP data pipelines for platforms such as Workday and enterprise systems Own end‑to‑end lifecycle of ERP data pipelines (ingestion → transformation → delivery) Support data conversion and migration initiatives (e.g., M&A, system integrations) Ensure pipeline reliability, recoverability, and stable production operations Troubleshoot pipeline failures and resolve root causes of data defects and operational issues Partner with business analysts and stakeholders to translate requirements into data solutions Implement and enforce SDLC best practices (version control, code reviews, CI/CD, release management) Develop and maintain data quality controls (freshness, completeness, anomaly detection, schema management) Detect and manage schema drift and downstream data issues proactively Build and maintain monitoring, alerting, and observability for data pipelines Optimize performance, scalability, and cost of data workloads Track operational KPIs (e.g., pipeline success rates, SLAs, incident trends, recovery times) Create runbooks, documentation, and audit‑ready operational processes Collaborate with data governance, security, and compliance teams on controls and data access Support analytics, reporting, and integration teams with reliable, well‑governed datasets Communicate effectively with technical and non‑technical stakeholders and escalate risks early