545 Process Analyst jobs in Fair Lawn,NJ

High School Diploma or General Equivalency Diploma.
2 years of relevant property claims adjusting experience of moderate complexity losses that includes writing estimates, involving dwelling and structural damages.
Advanced knowledge of estimating losses using Xactimate or similar tools and platforms.
Proficient knowledge of residential construction.
Proficient knowledge of property claims contracts and interpretation of case law and state laws and regulations.
Proficient negotiation, investigation, communication, and conflict resolution skills.
Proven investigatory, analytical, prioritizing, multi-tasking, and problem-solving skills.
Ability to travel 50-75% of the year (local & non-local) and/or work catastrophe duty when needed.
Acquisition and maintenance of insurance adjuster license within 90 days and 3 attempts.
Successful completion of a job-related assessment may be required.
Active Property & Casualty adjuster license

SmartExplore AI is experimental.

New, Posted 5 hours ago

General Merchandise Team Leader

Target Stores

Bronx, NY 10467

Flexible Schedule

New, Posted 1 day ago

Recommended

Property Adjuster Specialist - Field

USAA Careers

New York, NY 10025

New, Posted 1 day ago

Recommended

Senior Analyst, Corporate Strategy

ESPN Careers

New York, NY 10025

$162,200/yr

Merchandise Coordinator

HomeSense

East Hanover, NJ 07936

$16.92-$17.42/hr

OnsiteFlexible ScheduleChildcare AssistanceEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

1 year retail and 6 months of leadership experience
Able to work a flexible schedule, including nights and weekends
Capable of lifting heavy objects with or without reasonable accommodation
Superior communication and organizational skills with attention to detail
Team player, working effectively with peers and supervisors
Able to respond appropriately to changes in direction or unexpected situations
Able to train others

SmartExplore AI is experimental.

New, Posted 1 day ago

Apply Directly

Principal Quant Developer (MLOps)

Fidelity Investments

Lyndhurst, NJ 07071

OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field
Six (6) years of experience as a Senior Quant Developer or similar role
Alternatively, a Master's degree (or equivalent foreign education) in the same fields
Four (4) years of experience as a Lead Quantitative Development or similar role
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes