Frederick Fox

UJA-Federation of New York

Devana Cohen

Chief Investment Officer

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POSITION SUMMARYThe Investment Analyst, Quantitative Analytics and Technology will serve as a strategic analytics partner and internal consultant to the Investment Office, helping identify, design, build, and implement data-driven tools that support better investment decision-making across a complex, multi-asset class portfolio. This individual will work closely with investment professionals to understand workflows, translate analytical needs into practical solutions, and make high-quality investment analytics more accessible, intuitive, secure, and actionable.The role will also help advance the Investment Office’s existing data environment by managing existing data assets, adding and validating new data sources, and ensuring strong data integrity, governance, and security. This individual will assess emerging tools and technologies, manage relevant vendor relationships, and contribute to the evaluation of technology-related investment opportunities, including venture capital investments.MAJOR RESPONSIBILITIES<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Partner with the Investment Office to identify opportunities where data, analytics, automation, and technology can improve investment decision-making, operational effectiveness, and reporting. </li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Manage, maintain, and expand the Investment Office’s SQL database environment in Azure, including integrating data from multiple APIs, adding and validating new data sources, documenting data flows, monitoring data quality, managing access, and optimizing database performance.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Design, build, deploy, and maintain production-grade internal analytics tools, dashboards, data pipelines, and applications, including Streamlit and LLM based tools, that make investment data more accessible, customizable, secure, and actionable.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Evaluate emerging AI, machine learning, and automation tools as the ecosystem evolves, with a focus on ease of use, security, analytical quality, workflow efficiency, and relevance to Investment Office needs. Explore secure AI-enabled workflows and data-access frameworks that help investment professionals interact more effectively with approved data, analytics, and internal knowledge sources.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Participate actively in Investment Office meetings, contributing data-driven insights to support portfolio management, manager research, asset allocation, and investment evaluation.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Support the evaluation of technology-related investment opportunities, including venture capital investments; collaborate with departments across to share best practices; and complete ad hoc-related projects with a data-forward, analytical, and solutions-oriented approach.</li>
</ul>QUALIFICATIONSThe ideal candidate is a highly motivated, entrepreneurial, and technically sophisticated investment professional who combines analytical judgment with the ability to build practical, production-grade data and technology solutions. COMPETENCIES<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Strong technical proficiency in Python and SQL, with experience building and maintaining databases, data pipelines, APIs, dashboards, and analytics applications.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Experience working with cloud-based data environments, preferably Azure, including data ingestion, validation, documentation, access management, and performance optimization.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Demonstrated ability to design, build, deploy, and maintain production-grade internal tools or applications for business users; experience with Streamlit, Python-based analytics applications, and Excel-based workflows strongly preferred; experience with Tableau, Power BI, or similar visualization platforms a plus.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Familiarity with AI, machine learning, automation tools, LLM-enabled workflows, or emerging enterprise analytics technologies, including an understanding of data security, governance, and responsible use considerations.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Demonstrated analytical, quantitative, and problem-solving capabilities, with excellent attention to detail and a commitment to data accuracy, integrity, security, documentation, and responsible use of data and technology.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Collaborative and effective communicator with strong project-management skills, able to partner closely with a technically sophisticated investment team, translate analytical capabilities into practical investment applications, prioritize multiple projects, and operate effectively in a lean, high-impact team environment.</li>
</ul>REQUIREMENTS<ul style="margin:0px;padding-left:40px;">
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Bachelor’s degree required; graduate degree preferred in data science, computer science, engineering, applied mathematics, statistics, finance, business analytics, or a related quantitative field.</li>
<li style="line-height:1.2;font-family:Arial;font-size:14px;color:rgb(0, 0, 0);margin:0px;">Five or more years of relevant experience in data science, analytics engineering, software engineering, investment analytics, financial technology, quantitative research, or a related technical role.</li>
</ul>

POSITION SUMMARY

The Investment Analyst, Quantitative Analytics and Technology
will serve as a strategic analytics partner and internal
consultant to the Investment Office, helping identify, design,
build, and implement data-driven tools that support better
investment decision-making across a complex, multi-asset class
portfolio. This individual will work closely with investment
professionals to understand workflows, translate analytical needs
into practical solutions, and make high-quality investment
analytics more accessible, intuitive, secure, and actionable.

The role will also help advance the Investment Office’s existing
data environment by managing existing data assets, adding and
validating new data sources, and ensuring strong data integrity,
governance, and security. This individual will assess emerging
tools and technologies, manage relevant vendor relationships, and
contribute to the evaluation of technology-related investment
opportunities, including venture capital investments.

MAJOR RESPONSIBILITIES

* Partner with the Investment Office to identify opportunities
where data, analytics, automation, and technology can improve
investment decision-making, operational effectiveness, and
reporting.
* Manage, maintain, and expand the Investment Office’s SQL
database environment in Azure, including integrating data from
multiple APIs, adding and validating new data sources,
documenting data flows, monitoring data quality, managing access,
and optimizing database performance.
* Design, build, deploy, and maintain production-grade internal
analytics tools, dashboards, data pipelines, and applications,
including Streamlit and LLM based tools, that make investment
data more accessible, customizable, secure, and actionable.
* Evaluate emerging AI, machine learning, and automation tools as
the ecosystem evolves, with a focus on ease of use, security,
analytical quality, workflow efficiency, and relevance to
Investment Office needs. Explore secure AI-enabled workflows and
data-access frameworks that help investment professionals
interact more effectively with approved data, analytics, and
internal knowledge sources.
* Participate actively in Investment Office meetings,
contributing data-driven insights to support portfolio
management, manager research, asset allocation, and investment
evaluation.
* Support the evaluation of technology-related investment
opportunities, including venture capital investments; collaborate
with departments across to share best practices; and complete ad
hoc-related projects with a data-forward, analytical, and
solutions-oriented approach.
QUALIFICATIONS

The ideal candidate is a highly motivated, entrepreneurial, and
technically sophisticated investment professional who combines
analytical judgment with the ability to build practical,
production-grade data and technology solutions.

COMPETENCIES

* Strong technical proficiency in Python and SQL, with experience
building and maintaining databases, data pipelines, APIs,
dashboards, and analytics applications.
* Experience working with cloud-based data environments,
preferably Azure, including data ingestion, validation,
documentation, access management, and performance optimization.
* Demonstrated ability to design, build, deploy, and maintain
production-grade internal tools or applications for business
users; experience with Streamlit, Python-based analytics
applications, and Excel-based workflows strongly preferred;
experience with Tableau, Power BI, or similar visualization
platforms a plus.
* Familiarity with AI, machine learning, automation tools,
LLM-enabled workflows, or emerging enterprise analytics
technologies, including an understanding of data security,
governance, and responsible use considerations.
* Demonstrated analytical, quantitative, and problem-solving
capabilities, with excellent attention to detail and a commitment
to data accuracy, integrity, security, documentation, and
responsible use of data and technology.
* Collaborative and effective communicator with strong
project-management skills, able to partner closely with a
technically sophisticated investment team, translate analytical
capabilities into practical investment applications, prioritize
multiple projects, and operate effectively in a lean, high-impact
team environment.
REQUIREMENTS

* Bachelor’s degree required; graduate degree preferred in data
science, computer science, engineering, applied mathematics,
statistics, finance, business analytics, or a related
quantitative field.
* Five or more years of relevant experience in data science,
analytics engineering, software engineering, investment
analytics, financial technology, quantitative research, or a
related technical role.

Lead Analytics Engineer

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