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Manager Predictive Analytics Jobs in New York (NOW HIRING)

Fin

Risk Analyst

New York, NY · Remote

$100K - $175K/yr

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 ...

Jobtailor

Finance Data Analytics Specialist

Rahway, NJ · On-site

$80 - $120/hr

Familiarity with agile project management methods and Jira * Familiarity with AI and agentic AI systems * Understanding of advanced or predictive analytics * Understanding of data governance ...

New

Pwc

Deal Data Technology & Analytics, Manager

New York, NY · On-site

$99K - $232K/yr

... or predictive modeling/ML (Python, SAS) - Demonstrating proficiency in data analysis and visualization tools - Utilizing advanced skills in machine learning and predictive analytics - Managing ...

Forge Global

Analytics Manager

New York, NY · On-site

Forge Global is seeking an Analytics Manager to help shape the future of private market investing ... Develop predictive and statistical models that improve business outcomes. * Identify opportunities ...

NYU Langone Health

Senior Database Analyst

Manhattan, NY · On-site

$94K - $119K/yr

... analytics, machine learning, and AI-driven techniques to support predictive modeling and ... Maintain familiarity with new technologies for data management * Develop tools for temperature ...

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Manager Predictive Analytics information

What is a manager predictive analytics?

A Manager Predictive Analytics is a professional responsible for overseeing teams and projects that use statistical techniques, machine learning, and data analysis to forecast future trends and support business decision-making. They manage the development and implementation of predictive models, ensuring data quality and actionable insights for their organization. In addition to technical expertise, they coordinate with stakeholders to align analytics initiatives with business goals and often mentor data analysts or data scientists within their team.

What are the key skills and qualifications needed to thrive as a manager predictive analytics?

To thrive as a Manager Predictive Analytics, you need a strong background in statistics, data analysis, and predictive modeling, often supported by a degree in mathematics, statistics, computer science, or a related field. Expertise with analytics tools such as Python, R, SQL, and familiarity with machine learning platforms, as well as relevant certifications like SAS or AWS Certified Machine Learning, is typically expected. Outstanding leadership, communication, and problem-solving skills help in leading teams and translating complex insights for stakeholders. These abilities ensure data-driven decision-making, effective project management, and impactful business outcomes.

What are the main challenges faced by a manager predictive analytics, and how can they be addressed?

A Manager of Predictive Analytics often encounters challenges such as ensuring data quality, bridging communication gaps between technical teams and business stakeholders, and keeping up with rapidly evolving analytical tools and techniques. Addressing these challenges requires fostering strong cross-functional collaboration, implementing robust data governance practices, and encouraging continuous learning among team members. Additionally, setting clear project objectives and maintaining alignment with business goals can help deliver actionable insights and maximize the impact of predictive analytics initiatives.

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

AspectManager Predictive AnalyticsData Scientist
Required CredentialsBachelor's or Master's in Analytics, Statistics, or related field; often managerial certificationsBachelor's or Master's in Data Science, Statistics, or related field; sometimes PhDs
Work EnvironmentLeads teams, manages projects, collaborates with business unitsDevelops models, analyzes data, experiments with algorithms
Employer & Industry UsageBusiness, finance, marketing, healthcare organizationsTech companies, research institutions, finance, healthcare

While both roles focus on data analysis, the Manager Predictive Analytics oversees teams and strategic projects, whereas Data Scientists primarily develop models and conduct in-depth data analysis. The manager role emphasizes leadership and project management, often requiring experience in analytics tools and business acumen, while Data Scientists focus on technical expertise in algorithms and programming.

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 are popular job titles related to Manager Predictive Analytics jobs in New York?

For Manager Predictive Analytics jobs in New York, the most frequently searched job titles are:

What job categories do people searching Manager Predictive Analytics jobs in New York look for?

The top searched job categories for Manager Predictive Analytics jobs in New York are:

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

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

Manager Predictive Analytics jobs near you
Infographic showing various Manager Predictive Analytics job openings in New York as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Risk Analyst

Fin

New York, NY • Remote

$100K - $175K/yr

Full-time

Re-posted 6 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