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Executive Predictive Analytics Jobs in New York (NOW HIRING)

Fin

Risk Analyst

New York, NY · Remote

$100K - $175K/yr

This is a critical position, reporting directly to the CEO, and will require a combination of ... predictive analytics. * Ensure alignment with regulatory requirements, including AML, KYC, and ...

Bonfire Analytics

Staff Data Scientist

Manhattan, NY · On-site

$150 - $200/hr

Advanced analytics & modeling - design and execute statistical analyses, predictive models, and ... executive audiences * Experience with medical or prescription claims, provider databases, or ...

Fin

Risk Analyst

New York, NY · On-site +1

$100K - $175K/yr

This is a critical position, reporting directly to the CEO, and will require a combination of ... predictive analytics. * Ensure alignment with regulatory requirements, including AML, KYC, and ...

The New York Times

Senior Analyst, Total Rewards

New York, NY · On-site

$90K - $118K/yr

... and predictive analytics. * Develop sophisticated models for variable pay (AIP/LTI) and annual ... Build and maintain automated Total Rewards benchmarking tools and executive dashboards. * Lead the ...

MSD

Dir, Patient Intelligence Lead

Rahway, NJ · On-site

Reporting to the Executive Director, Digital Patient Experience, the Director, Patient Intelligence Lead is a pivotal new role dedicated to building our predictive patient analytics capabilities.

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Executive Predictive Analytics information

What is an executive predictive analytics?

Executive Predictive Analytics refers to the use of advanced data analysis techniques and machine learning models by organizational leaders to forecast future business outcomes and inform strategic decisions. Executives use predictive analytics to anticipate market trends, identify risks and opportunities, and optimize resource allocation. This role requires a combination of business acumen, data science knowledge, and the ability to translate complex data into actionable insights for high-level decision-making.

How does an executive predictive analytics professional typically collaborate with other departments to drive business outcomes?

An Executive Predictive Analytics professional often works closely with teams across marketing, finance, operations, and IT to align advanced analytics initiatives with broader business goals. They translate complex data insights into actionable strategies, facilitating data-driven decision-making at the executive level. Regular cross-functional meetings and workshops are common to ensure that predictive models are integrated into business processes and that stakeholders understand their impact. Collaboration is key, as these executives must communicate technical findings in an accessible way to influence strategic planning and organizational change.

What are the key skills and qualifications needed to thrive as an executive in predictive analytics, and why are they important?

To thrive as an Executive in Predictive Analytics, you need advanced expertise in statistical analysis, data modeling, and business strategy, usually supported by a degree in data science, statistics, or a related field. Familiarity with analytics platforms such as SAS, R, Python, and big data tools, as well as certifications like Certified Analytics Professional (CAP), is highly beneficial. Exceptional leadership, communication, and strategic decision-making abilities set standout executives apart in this field. These skills enable leaders to drive data-informed organizational growth, align analytics initiatives with business objectives, and foster innovation across teams.

What is the difference between Executive Predictive Analytics vs Data Scientist?

AspectExecutive Predictive AnalyticsData Scientist
Required CredentialsOften requires advanced degrees in business, analytics, or related fields; certifications in analytics toolsTypically requires degrees in computer science, statistics, or mathematics; certifications in programming and data analysis
Work EnvironmentStrategic, executive-level settings; focuses on business impact and decision-makingTechnical environment; involves data modeling, coding, and statistical analysis
Employer & Industry UsageUsed in corporate strategy, finance, marketing, and operations departmentsEmployed across tech, finance, healthcare, and research organizations

While both roles involve data analysis and predictive modeling, Executive Predictive Analytics focuses on strategic insights for leadership decision-making, whereas Data Scientists handle technical data modeling and algorithm development. The roles often overlap but differ mainly in scope and target audience.

What are the most commonly searched types of Predictive Analytics jobs in New York?

The most popular types of Predictive Analytics jobs in New York are:

What cities in New York are hiring for Executive Predictive Analytics jobs?

Cities in New York with the most Executive Predictive Analytics job openings:

Executive Predictive Analytics jobs near you
Infographic showing various Executive Predictive Analytics job openings in New York as of July 2026, with employment types broken down into 1% Internship, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Risk Analyst

Fin

New York, NY • Remote

$100K - $175K/yr

Full-time

Re-posted 24 days ago

Job description

About Fin

Fin is a next-generation payments platform built for high-value, global, and instant transactions. We are a Series A-stage company backed by Sequoia, Circle, and other notable investors. Powered by stablecoins, Fin enables users and businesses to move millions of dollars in seconds - whether to other Fin users, directly into bank accounts, or across crypto rails. By combining the speed of crypto with the reliability and trust of traditional finance, Fin reimagines how money moves worldwide. If banks and payment products were reinvented today, they would look like Fin.

Role Overview

We are hiring our first  Fraud/Risk Analyst to join our Risk & Compliance team . This role will focus on identifying, analyzing, and mitigating risks associated with digital asset transactions – including ACH fraud and compliance with applicable regulations like the Patriot Act and Bank Secrecy Act. This is a critical position, reporting directly to the CEO, and will require a combination of technical, analytical, and regulatory expertise to build a robust fraud detection and risk assessment framework from the ground up.

Key Responsibilities

  • Develop and implement a comprehensive risk management strategy tailored to the evolving digital asset landscape.

  • Take action to resolve automatically flagged transactions and individuals

  • File suspicious activity reports as required 

  • Monitor and analyze transaction data to detect potential fraud, suspicious activities, and emerging risk trends.

  • Utilize advanced data analysis techniques and fraud detection tools to identify anomalies and potential security threats.

  • Create and maintain risk assessment models to evaluate the financial and reputational impact of potential fraud incidents.

  • Partner with the engineering team to design and implement fraud detection systems, leveraging machine learning and predictive analytics.

  • Ensure alignment with regulatory requirements, including AML, KYC, and digital asset regulations.

  • Draft detailed reports and dashboards on risk findings, fraud incidents, and risk mitigation strategies for senior leadership and stakeholders.

  • Lead cross-functional risk assessments for new product launches, ensuring security and fraud prevention measures are integrated into product design.

  • Stay abreast of emerging risks in the digital asset space, including regulatory changes and new fraud tactics.

  • Develop incident response plans for fraud detection and participate in incident response drills to assess and enhance our risk management framework.

Qualifications

  • Bachelor's degree in Finance, Economics, Computer Science, Data Science, or related field.

  • 5+ years of experience in fraud analysis, risk management, or financial crime prevention, ideally within fintech, digital assets, or blockchain environments.

  • Demonstrated experience with fraud detection systems, transaction monitoring tools, and data analysis platforms (SQL, Python, R).

  • Strong knowledge of digital asset platforms, blockchain technology, and stablecoin ecosystems.

  • Experience with regulatory compliance, particularly regarding AML, KYC, and financial crime prevention.

  • Exceptional analytical and problem-solving skills with a data-driven approach to decision-making.

  • Strong written and verbal communication skills, with the ability to clearly articulate complex risk findings to non-technical stakeholders.

Preferred Qualifications

  • Certifications such as Certified Fraud Examiner (CFE), Certified Risk Manager (CRM), or CAMS.

  • Experience with machine learning models for fraud detection and predictive analytics.

  • Familiarity with incident response protocols and risk mitigation frameworks in financial services.

  • Prior experience in a fast-paced startup or scaling fintech environment.

Compensation Range: $100K - $175K