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Predictive Modeling Jobs in Rhode Island (NOW HIRING)

Varsity Tutors

Data Science Tutor

Providence, RI · Remote

$40/hr

Guides students through data cleaning with Pandas, exploratory analysis with visualization libraries, building predictive models, conducting statistical tests, and creating compelling data ...

Intraedge

Google Cloud Platform Engineer

Woonsocket, RI · On-site

... model lifecycle, monitoring, or AI-driven alerting) Preferred Qualifications * Google Cloud ... Exposure to AIOps tools, anomaly detection, or predictive analytics systems * Experience with large ...

New

SEACORP

Senior AI/ML Engineer

Middletown, RI

$104K - $142K/yr

Develop predictive, classification, anomaly detection, and data augmentation models. * Establish AI engineering standards, MLOps pipelines, and reusable corporate AI infrastructure. * Support SEACORP ...

Indeed

Machine Learning Engineer III

Providence, RI

On a daily basis, you will explore data and formulate problem statements, develop and deploy predictive models while monitoring them in production, and guide the team on the same. Additionally, you ...

Varsity Tutors

Machine Learning Tutor

Providence, RI · Remote

$40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Smartapp

Product Analyst

East Greenwich, RI · On-site

Strong understanding and implementation of predictive / analytical modeling techniques, theories, principles, and practices preferred. * Capable of delivering on multiple competing priorities with ...

Smartapp

Product Analyst

East Greenwich, RI

Strong understanding and implementation of predictive / analytical modeling techniques, theories, principles, and practices preferred. * Capable of delivering on multiple competing priorities with ...

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All JobsPredictive Modeling JobsPredictive Modeling Jobs in Rhode Island

Predictive Modeling information

See Rhode Island salary details

$10

$57

$81

How much do predictive modeling jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for predictive modeling in Rhode Island is $57.50, according to ZipRecruiter salary data. Most workers in this role earn between $51.54 and $66.88 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Predictive Modeling position, and why are they important?

To thrive in Predictive Modeling, you need strong statistical analysis, data mining, and machine learning skills, often supported by a degree in statistics, computer science, mathematics, or a related field. Expertise with tools such as Python, R, SAS, or SQL, as well as knowledge of data visualization software, is commonly required, and certifications in data science or analytics are a plus. Strong problem-solving abilities, attention to detail, and effective communication are key soft skills for this role. Mastering these skills enables professionals to build accurate models, interpret data-driven results, and clearly communicate insights to stakeholders, which are critical for informed business decision-making.

What is a Predictive Modeling job?

A Predictive Modeling job involves using statistical techniques, machine learning algorithms, and data analysis to forecast future outcomes based on historical data. Professionals in this role build and test models to identify patterns, trends, and relationships in complex datasets. They commonly work in industries like finance, healthcare, and marketing to improve decision-making and optimize business processes. Strong skills in programming, data manipulation, and statistical analysis are essential for success in this role.

What is a predictive modeler?

A predictive modeler is a professional who develops statistical and machine learning models to forecast future outcomes based on historical data. They use tools like Python, R, or specialized software and often require knowledge of data analysis, statistics, and programming. Their work supports decision-making in various industries such as finance, marketing, and healthcare.

What jobs make $1,000,000 a year?

In predictive modeling, high-earning roles such as senior data scientists, machine learning engineers, and analytics directors can reach or exceed $1 million annually, especially in top tech companies or financial firms. These positions typically require advanced skills in statistical analysis, programming, and experience with big data tools, along with leadership responsibilities and often performance-based bonuses or equity.

Is 40 too late for data science?

Predictive modeling is a key role in data science, and age is not a barrier to entering the field. Many professionals transition into data science later in their careers by developing skills in programming, statistics, and tools like Python or R. Continuous learning and relevant experience are more important than age when pursuing a data science career.

What does a typical workday look like for someone working in predictive modeling?

A typical day in predictive modeling involves gathering and cleaning data, selecting relevant features, and building statistical or machine learning models to forecast trends or behaviors. You’ll regularly use programming languages and analytics tools to test model performance and iterate on results, while documenting findings and preparing reports for internal teams or clients. Collaboration is often required with data engineers, subject matter experts, and business leaders to ensure that models align with organizational goals. Additionally, you may be tasked with presenting your insights to both technical and non-technical audiences, making strong communication skills essential for success in this role.

What job makes $10,000 a month without a degree?

Predictive modeling roles, such as data scientists or machine learning engineers, can earn $10,000 or more per month with significant experience and expertise in statistical analysis, programming, and data tools. These jobs often require strong skills in Python, R, or SQL and may involve working in tech, finance, or consulting environments, but typically do not require a formal degree if skills are demonstrated through portfolios or certifications.
What are the most commonly searched types of Predictive Modeling jobs in Rhode Island? The most popular types of Predictive Modeling jobs in Rhode Island are:
What are popular job titles related to Predictive Modeling jobs in Rhode Island? For Predictive Modeling jobs in Rhode Island, the most frequently searched job titles are:
What job categories do people searching Predictive Modeling jobs in Rhode Island look for? The top searched job categories for Predictive Modeling jobs in Rhode Island are:
Predictive Modeling jobs near you
Solution Engineering Manager- Financial Data Repository

Solution Engineering Manager- Financial Data Repository

Citizens Bank

Johnston, RI • On-site

Full-time

Posted 3 days ago

Job description

Job Description
We are looking for a Solution Engineering Manager to lead a team of engineers in supporting Finance Data Repository (FDR)-the enterprise data backbone powering Treasury, Finance, and Regulatory analytics. This role requires a strategic thinker with strong technical leadership and deep understanding of financial data architecture, Finance, Treasury and Tax functions, regulatory reporting requirements, and modern AI/ML patterns applied to financial data. The ideal candidate bridges the gap between Finance business stakeholders and engineering teams, ensuring solutions are technically sound, regulatory-grade, and aligned with enterprise objectives. The candidate will oversee the end-to-end solution development process-from requirements gathering with Finance and Treasury users, through data model design, pipeline engineering, system integration, AI feature enablement, and post-deployment support. They will work closely with Finance, Technology and vendor teams to ensure FDR solutions are feasible, scalable, and deliver value across the enterprise. They will also play a key role in mentoring and developing the team, fostering a culture of innovation, collaboration, and continuous improvement. The ability to communicate complex financial and technical concepts in a clear and compelling manner will be essential in building trust with business stakeholders, regulators, and engineering partners. Applicants should have a proven profile that combines practitioner depth + cross-finance expertise + technical fluency + AI/ML engineering awareness and translates complex financial behavior into scalable, governed, intelligent data solutions. The Solution Engineering Manager will serve as the primary point of contact between the engineering team and business stakeholders across Finance, and Technology.
Key Responsibilities
Data Architecture & Financial Domain Engineering
  • Establish authoritative data models enabling consistency across management and regulatory outputs
  • Drive alignment between Finance data domains to support enterprise analytics, reporting, and AI-driven decisioning
  • Translate financial concepts into data models and technical solutions; work closely with engineering and data teams
  • Engineer data structures and pipelines supporting Finance, Treasury, Insurance, and Tax data
  • Design and govern semantic data layers that enable consistent KPI definitions , governed feature reuse across AI/ML models, and natural language query (NLQ) access to finance data
AI & Intelligent Analytics Enablement
  • Architect the data foundation that powers AI use cases across Finance and Treasury, including:
    • NLQ / Conversational Analytics: Enable natural language queries against FDR datasets (profitability, liquidity, balance sheet) so analysts can retrieve insights without SQL or analyst support
    • ML-Driven Data Quality & Anomaly Detection: Implement machine learning models that proactively detect data anomalies, reconciliation breaks, and reporting errors before they reach production
    • RAG Pipelines & Document Intelligence: Support retrieval-augmented generation (RAG) architectures that connect regulatory documents, loan agreements, and financial contracts to structured FDR data for AI-powered extraction and summarization
    • AI-Ready Feature Engineering: Ensure FDR delivers consistent, governed feature definitions reduce feature drift across predictive models
    • Agentic Workflows & Automation: Enable AI-driven workflow routing, automated reconciliation, and intelligent exception handling that reduce manual intervention in close cycles and regulatory reporting
  • Partner with the GenAI Council and AI Excellence teams to align FDR data products with enterprise AI roadmap and use case prioritization
Team Leadership & Talent Development
  • Lead, mentor, and develop a team of data engineers and solution engineers building FDR platform components
  • Foster a culture of technical excellence, accountability, and continuous improvement
  • Manage capacity planning, resource allocation, and workload balancing across concurrent initiatives
  • Upskill team on AI/ML engineering patterns, including vector search, embeddings, LLM integration, and governed feature stores

Delivery & Platform Engineering
  • Oversee end-to-end design, engineering, and support of the FDR platform
  • Translate complex financial business logic into scalable, governed data engineering solutions
  • Manage project timelines, resources, and deliverables across concurrent workstreams
  • Lead integration with enterprise platforms including:
    • Treasury modeling systems (QRM)
    • BI/analytics tools (Power BI, Tableau)
    • AI/ML serving layers and LLM orchestration frameworks
  • Drive modernization from legacy platforms into cloud-native, automated architectures
  • Build API-driven and event-based integrations supporting daily and monthly production cycles
Regulatory, Controls & Governance
  • Deliver regulatory-grade datasets supporting internal and external reporting
  • Implement source-to-report data lineage, reconciliation logic, and validation frameworks
  • Ensure all outputs meet SOX, RDAR, and audit expectations
  • Implement within pipelines: data quality monitoring and anomaly detection / reconciliation frameworks (GL, sub-ledger, cross-system balance checks) / full metadata, lineage, and audit traceability
  • Ensure AI model outputs are explainable, auditable, and aligned with regulatory expectations
  • Align platform outputs to regulatory and internal control standards
Stakeholder Engagement & Process Improvement
  • Partner with Treasury, Finance, Tax, and Technology to define requirements, assess feasibility, and ensure scalability
  • Present solutions and progress to senior leadership and regulatory stakeholders
  • Support pre-implementation activities including vendor evaluation, competitive analysis, and solution demonstrations
  • Continuously refine engineering processes, methodologies, and tools to enhance delivery efficiency, data quality, and platform reliability
  • Stay current with industry trends, emerging technologies, AI/ML advancements, and cloud/enterprise data platforms
Requirements
Education
  • Bachelor's degree in Engineering, Computer Science, Finance, or related field
Experience
  • 10+ years in data engineering, platform engineering, or financial systems integration
  • 5+ years in a leadership or management position overseeing engineering teams
  • Proven track record delivering complex, multi-system financial data platforms in regulated environments
  • 2+ years hands-on experience with AI/ML engineering, data science infrastructure, or intelligent automation in a financial services context
Technical Expertise
  • Strong hands-on experience with:
    • Snowflake, Spark, Microservices
    • Data pipeline frameworks (ETL/ELT), cloud data platforms, large-scale data processing
    • Enterprise data architecture patterns (data lake → curated layers → consumption)
  • AI/ML Technical Proficiency:
    • LLM orchestration frameworks (LangChain or equivalent)
    • Vector databases and embedding stores (FAISS, Pinecone, or similar) for RAG and semantic search
    • ML-driven data quality frameworks and anomaly detection models
    • Semantic layer design for AI/ML feature consistency and NLQ enablement
    • Familiarity with cloud AI services (AWS Bedrock, Azure OpenAI, or equivalent)
  • Experience with Treasury or financial platforms (QRM)
Finance & Treasury Domain Knowledge
  • Strong working knowledge of:
    • ALM, FTP, liquidity management, cash flow modeling
    • Interest rate risk concepts (repricing, yield curves, spreads)
    • RWA, Economic Capital, and regulatory reporting frameworks
    • FR 2052a and capital/liquidity stress testing
    • Financial product structures (loans, deposits, derivatives, investment securities)
Soft Skills & Leadership
  • Excellent communication and interpersonal skills-ability to translate complex technical, financial, and AI concepts for diverse audiences
  • Proven ability to manage multiple projects and competing priorities simultaneously
  • Experience working with cross-functional teams across Finance, Risk, Technology, and AI/Data Science organizations
  • Strong problem-solving and analytical skills

Hours & Work Schedule
  • Hours per Week: 40
  • Work Schedule: Monday - Friday
  • Hybrid: 4 days per week onsite, 1 day remote

About Us
Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Equal Employment and Opportunity Employer
Job Applicant Data Privacy Policy
Background Check
Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.

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