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1mo ago

SQL Data Analyst

Motion Recruitment Charlotte, NC

Charlotte, NC

1mo ago Closed

Contract Data Analysis Data Analytics Database

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Long-term contract SQL Data Analyst role in Charlotte, NC (hybrid) for a financial services client, focused on analytics and financial crimes/AML model support.

Responsibilities

Consult on complex initiatives with broad impact and large-scale planning for Analytics.
Review and analyze multi-faceted, larger-scale analytics challenges requiring evaluation of multiple factors.
Contribute to resolution of complex situations by applying knowledge of function, policies, procedures, and compliance requirements tied to deliverables.
Strategically collaborate and consult with client personnel.
Perform in-depth analysis on AML models, including:
- Customer Risk
- Product Risk
- AML Country Risk
- Industry Risk
Communicate findings with peers, managers, and stakeholders.
Participate in initiatives with broad impact as a key participant in large-scale planning.
Implement and maintain components of an effective financial crimes program aligned with applicable laws, regulations, and regulatory expectations, including:
- Bank Secrecy Act
- Anti-Money Laundering
- Counter Terrorist Financing
- Global Sanctions
- Fraud
Create, update, and maintain processes and procedures to support awareness of schemes and trends.
Review and examine complex business challenges requiring evaluation of multiple factors.
Conduct or lead investigative research, including root cause examination and consulting on transactions, suspicious situations, policy violations, referrals, customers, and related parties presenting moderate to high risk or complexity.
Support implementation of initiatives with moderate to high risk.
Provide guidance for the development and delivery of training.
Advise on complex matters using policies, procedures, and compliance requirements to guide a broader work team and drive new initiatives.
Partner with more experienced leaders to develop innovative methods and strategy adjustments to minimize portfolio risk and maximize profits.
Collaborate with peers, colleagues, and managers to resolve issues and achieve goals.
Inform peers, line of business, and other external partners on analysis findings.

Requirements

5+ years of experience using SQL to query large transactional databases, with ability to write, edit, and run queries.
5+ years of Analytics experience, or equivalent demonstrated through one or a combination of: work or consulting experience, training, military experience, or education.

Desired Skills & Experience

Corporate Risk Experience / Financial Crimes.
3+ years of experience analyzing, tracking/monitoring, and reporting data within the Financial Crimes industry.
Prior experience producing and reviewing business intelligence reporting.
In-depth experience and understanding of databases and information technologies.
Ability to influence and collaborate with Senior Leadership on an enterprise level.
Experience defining requirements for large projects.

Tech

Benefits

Competitive benefit package

Contract details: Long-term contract (12+ months). Location: Charlotte, NC 28202 (hybrid). Experience: 5+ years.

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1mo ago

Senior Machine Learning Engineer

Motion Recruitment Wilmington, MA

Wilmington, MA

1mo ago Closed

Full time Senior Artificial Intelligence Data Analysis

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Motion Recruitment is hiring a Senior Machine Learning Engineer in Wilmington, MA for an onsite role focused on bringing machine learning from raw sensor data to models that run reliably on constrained hardware. This position spans the end to end ML lifecycle, including data pipelines, model development, deployment to edge, and the supporting MLOps infrastructure needed for regulatory and quality workflows.

In this role, you will work with sensor and embedded teams to train and optimize signal processing and anomaly detection models, then integrate and validate inference directly within device software. You will also help shape how sensor data is selected, validated, collected, and organized so model performance can be tracked and improved over time.

Key responsibilities

Own the full machine learning lifecycle, from raw sensor data to models running on constrained hardware.
Design and use data pipelines for sensor data.
Train, optimize, and deploy machine learning models for signal processing and anomaly detection on edge devices.
Collaborate with embedded engineers to integrate and validate inference within device software.
Build MLOps infrastructure to support regulatory and quality processes.
Participate in sensor selection and validation.
Document model development to support regulatory submissions and internal quality processes.
Develop and troubleshoot workflows for collecting, cleaning, and organizing sensor data.
Build and refine ML models for real-time device applications and performance improvements.
Work with firmware teams to embed and test AI features on hardware platforms.
Set up and oversee tools for tracking experiments, automating evaluations, and managing deployments.
Analyze model behavior, ensure reliability, and resolve issues to maintain high-quality outputs.

Required skills and experience

Python proficiency.
Hands-on experience with PyTorch or TensorFlow.
Experience deploying models to edge using TFLite, ONNX, CoreML, TensorRT, or an equivalent approach.
Experience building sensor data pipelines.
Proficiency with MLOps.
Solid software engineering fundamentals.
Proficiency in C or C++.

Desired skills and experience

5 years of machine learning engineering or applied ML.
Experience with physiological signal processing for medical or wearable applications.
Background in robotics or autonomous systems.
Experience in a startup or small team.
Degree in a relevant field.

Tools and technologies

Python, PyTorch, TensorFlow
TFLite, ONNX, CoreML, TensorRT
MLOps
C, C++

Compensation and benefits

Bonus OR Commission eligible
Medical Insurance
Dental Benefits
Vision Benefits
Paid Time Off (PTO)
401(k) {including match - if applicable}

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1mo ago

Machine Learning Engineer - AI Trainer

DataAnnotation Massachusetts 🇺🇸 Remote

Massachusetts

1mo ago Closed

$50 - $100/hr Contract Ai Ml Ai Model Training Ai Training

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

DataAnnotation is seeking an experienced Machine Learning Engineer - AI Trainer to evaluate and help train AI systems focused on quantitative reasoning. This is a remote contract opportunity based in Massachusetts, with flexible project selection and work timing after completing a short assessment.

Key Responsibilities

Review AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, ensuring both technical accuracy and real-world validity.
Develop and solve quantitative problems used to train and benchmark AI systems, covering areas such as forecasting, experimental analysis, optimization, and statistical inference.
Produce clear technical explanations and well-documented analytical code.
Provide feedback that informs and improves the next generation of AI models built for quantitative reasoning.

Required Qualifications

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a closely related field.
Some coding experience with the ability to write and review analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design, including examples like A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
English fluency at native or bilingual level, along with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar). A master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise.

Technologies

Kaggle
AWS
GCP

Compensation and Employment Details

Job type: Contract
Location: Massachusetts (remote)
Pay: USD 50–100 per hourly (projects are paid hourly, up to $60 USD per hour, with potential for higher-paying projects based on performance)
Experience level: Minimum 2 years

Remote Work and Availability

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects to take on and when you work.

Assessment Process

After you sign up for an account, you’ll complete a short assessment as a version of an interview. If you pass, you will receive an email confirmation and paid work will become available on the platform.

Additional Notes

Payment is made via PayPal.
DataAnnotation will never ask for any money from you.

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1mo ago

Machine Learning Engineer - AI Trainer

DataAnnotation New York, NY 🇺🇸 Remote

New York, NY

1mo ago Closed

$50 - $100/hr Full time Ai Ml Ai Training Artificial Intelligence

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

DataAnnotation is seeking an experienced Machine Learning Engineer - AI Trainer to evaluate and help train AI systems focused on quantitative reasoning and analytical tasks. This position is fully remote, with paid hourly work and scheduling flexibility.

Role Overview

You will assess AI-generated quantitative outputs for both technical correctness and real-world usefulness. The work also includes designing quantitative problem sets that support training and benchmarking of AI systems across forecasting, experimental analysis, optimization, and statistical inference.

Responsibilities

Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, ensuring technical accuracy and practical validity.
Design and solve quantitative problems used to train and benchmark AI systems, covering areas such as forecasting, experimental analysis, optimization, and statistical inference.
Write clear technical explanations and maintain well-documented analytical code.
Deliver feedback that informs the development of next-generation AI models for quantitative reasoning.

Requirements

2+ years of hands-on experience in a quantitative role or research environment, such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or a closely related field.
Some coding experience, with comfort writing and reviewing analytical code end-to-end.
Practical experience with statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting.
Fluency in English (native or bilingual), with strong writing skills.
A bachelor’s degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar). A master’s or PhD is a plus.
Relevant credentials are a plus, such as Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent evidence of expertise.

Technologies

PayPal
AWS
GCP
Kaggle

Compensation and Schedule

Location: New York, NY (remote)
Salary: USD 50 - 100 per hourly
Work type: paid hourly (projects paid hourly, up to $60 USD per hour)
Schedule: flexible schedule, with choice of which projects you take on and when you work

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
Flexible schedule: choose which projects to take on and when to work.
Competitive pay: hourly projects, up to $60 USD per hour.
Growth potential: opportunities for higher-paying projects with strong performance.
Impact: contribute to AI systems built to reason about data and analytics.

Additional Notes

Payment is made via PayPal.
They will never ask for any money from applicants.
The role is available only to applicants in the US, Canada, UK, Ireland, Australia, and New Zealand.

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1mo ago

Machine Learning Engineer - AI Trainer

DataAnnotation Washington, DC 🇺🇸 Remote

Washington, DC

1mo ago Closed

$50 - $100/hr Full time Ai Ml Ai Model Training Ai Trainer

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Join DataAnnotation as a Machine Learning Engineer - AI Trainer to evaluate and help train AI systems focused on quantitative reasoning.

Responsibilities

Review AI-generated quantitative outputs, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity
Create and solve quantitative problems used to train and benchmark AI systems across forecasting, experimental analysis, optimization, and statistical inference
Produce clear technical explanations alongside well-documented analytical code
Deliver feedback that informs and improves the next generation of AI models for quantitative reasoning tasks

Requirements

2+ years of hands-on experience in a quantitative role or research environment (data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or related)
Coding experience required, with comfort writing and reviewing analytical code end-to-end
Practical experience with statistical methods, predictive modeling, and experiment design, including examples such as A/B testing, hypothesis testing, regression, classification, and time-series forecasting
English fluency (native or bilingual level) with strong writing skills
Bachelor’s degree in a quantitative field preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); master’s or PhD is a plus
Relevant credentials are a plus, such as Kaggle Competition ranking or AWS/GCP ML certifications (or equivalent demonstrated expertise)

Benefits

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand
Flexible schedule: choose which projects to take on and when you work
Competitive pay: paid hourly; up to $60 USD per hour for strong performance (salary range listed: USD 50 - 100 per hourly)
Impact: help shape AI systems that reason about data and analytics

Additional Information

Payment method: PayPal
No money will be requested from applicants
This role is available only to candidates located in the US, Canada, UK, Ireland, Australia, and New Zealand

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1mo ago

Data Engineer - Financial Industry

Code Willing, LLC New Orleans, LA

New Orleans, LA

1mo ago Closed

$70k - $80k/yr Full time Python Apache Airflow Big Data

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

Code Willing, LLC is hiring a Junior or Mid-Level Data Engineer to support data engineering needs in the financial industry in a hybrid setup based in New Orleans, LA 70130. In this role, you will design and optimize big data ETL pipelines, strengthen data quality practices for financial datasets, and help stakeholders by keeping communications clear and project updates timely.

Role Focus

You will work on financial industry datasets and build reliable data workflows that support areas including security reference data, end-of-day pricing, and trade/quote data. The scope primarily covers Equities, Futures and Fixed Income.

Responsibilities

Design, implement, and refactor efficient big data ETL pipelines in Apache Airflow.
Optimize and expand an existing Python-based data analysis code base.
Develop highly performant data ETL and analysis applications using multiprocessing and multithreading.
Develop and enhance a Data Quality code base and standards for Financial Industry datasets.
Provide data support to stakeholders, maintaining transparent communication and timely project updates.
Stay current on emerging data engineering trends and technologies and contribute to continuous improvement of data practices.

Requirements

Bachelor’s degree in Computer Science, Mathematics, or a related field; equivalent work experience may be considered in lieu of specific education requirements.
2+ years of hands-on experience with Python and 2+ years with SQL in a professional setting.
Experience with Git and Linux.
Experience processing and managing large datasets.
Knowledge of financial industry data, especially security reference data, end-of-day pricing, and trade/quote data (with focus on Equities, Futures, and Fixed Income).
Strong analytical skills with the ability to collaborate across departments and teams.
Excellent problem-solving skills and strong attention to detail, especially for performance tuning and optimizing data workflows.

Technologies

Apache Airflow
Python
SQL
Git
Linux
Multiprocessing
Multithreading
Claude Code

Benefits

401(k)
401(k) matching
Dental insurance
Flexible spending account
Health insurance
Health savings account
Life insurance
Paid time off
Vision insurance

Preferred Qualifications

Certifications in AWS, Data Analytics, or similar technologies.
Claude Code and Agent experience.
A working knowledge or experience working with Claude Code or equivalent tools.

Job type: Full-time. Location: Hybrid remote in New Orleans, LA 70130. Compensation: USD 70,000 - 80,000 per year.

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1mo ago

Data Scientist

PayPal Chicago, IL

Chicago, IL

1mo ago Closed

$97k - $180k/yr Full time Analytics Business Analytics Business Intelligence

This position is no longer accepting applications (closed Sep 15, 2026).

Job Description

PayPal is hiring a Data Scientist in Chicago, IL (hybrid) to analyze large datasets, develop and evaluate statistical and machine learning models, and improve fraud and portfolio outcomes.

Responsibilities

Analyze and process large datasets using statistical software.
Use sampling approaches to define groups for study or apply complete enumeration methods.
Build, compare, and evaluate statistical and machine learning models using performance metrics.
Apply mathematical principles and statistical methods to address scientific and applied problems.
Analyze business and financial data to identify and resolve operational issues.
Identify trends and relationships among variables across datasets.
Work across a portfolio of projects including card risk strategies, acquisition, and payment risk strategies.
Partner with stakeholders across Credit Risk, Product, and Engineering to optimize fraud strategies and portfolio performance.
Analyze and assess emerging fraud trends and propose mitigation strategies.
Maintain and develop Monitoring and Alerting capabilities to monitor CBMC program health and simplify insights for key stakeholders.
Provide regular updates to senior leaders on Portfolio Health, highlights, lowlights, and actionable insights.
Own end-to-end management of fraud loss and decline rates.
Collaborate with cross-functional teams to develop fraud prevention and loss-saving strategies and optimize transaction declines.
Produce periodic KPI reports summarizing business units’ risk and control environment for senior management.

Requirements

Master’s degree (or foreign equivalent) in Computer Science, Engineering, Management Information Systems, or a closely related field plus two (2) years of experience in the job offered or a related occupation.
2 years of experience with basic analytics.
2 years of experience in fraud risk management within the financial services industry.
2 years of experience writing SQL queries to analyze large datasets.
2 years of experience building interactive dashboards and visual reports using Tableau.
2 years of experience using MS Excel and Pivot Tables to create analytical views and summarize data.
2 years of experience using visualization tools to communicate analytical insights.
1 year of experience applying machine learning methods.
1 year of experience applying data science techniques to solve real-world problems.
1 year of experience using Python to analyze large datasets.
Legally authorized to work in the U.S. without sponsorship.

Technologies

SQL
Tableau
MS Excel
Pivot Tables
Python

Benefits

Comprehensive, choice-based programs to support personal wellbeing across physical, emotional, and financial needs.
Generous paid time off.
Healthcare coverage for you and your family.
Resources to support financial security and mental health.