Worth AI

Data Scientist

• - Actively develop (code) machine learning or statistical models in a cloud environment, and work with engineering teams to deploy and optimize them in a production state
• - Connect systems and large data sets across the company to develop predictive models that adjust to emerging customer, economic, and business trends
• - Monitor performance of models with respect to accuracy and retrain as necessary, while also leveraging new data sources as they become available
• - Mine data from multiple source systems to support internal analysis as required
• - Regularly present or demo recent work to executive and product teams

Senior Data Scientist

Support Engineer

• Research, identify, and implement solutions to customer issues in our applications.
• Analyze support trends and propose process or product improvements to reduce future incidents.
• Timely escalation of unresolved issues to appropriate stakeholders and teams.
• Provide prompt, accurate, and level-headed feedback to internal and external stakeholders.
• Provide alternative procedures when standard procedures are insufficient in order to ensure issues are being resolved in a timely fashion.
• Prioritize and manage several open issues at one time.
• Build and maintain tooling to support timely issue resolution and issue prevention.

Technical Support Engineer

Data Analyst

• Mine and analyze large-scale credit, transactional, and behavioral datasets to identify trends, anomalies, and insights that inform credit risk, underwriting, fraud, and pricing strategies.
• Write performant SQL queries to extract, transform, and analyze data across structured and semi-structured sources (including loan-level, customer, and bureau data).
• Design, build, and maintain interactive dashboards and reporting tools to support Finance, Risk, Credit, and Executive teams in monitoring key performance indicators.
• Partner with Data, Finance, Product and Engineering teams to define and track key metrics for credit performance, loss forecasting, and portfolio health.
• Support the development and ongoing evaluation of AI/ML models by providing exploratory data analysis, historical performance context, and business rule validation.
• Collaborate with data engineering and data science teams to ensure pipelines are reliable, secure, and meet both operational and regulatory standards.
• Automate recurring reports and analyses to improve visibility and reduce manual workflows across the credit and finance lifecycle.
• Contribute to model governance efforts by ensuring documentation, auditability, and transparency of data inputs used in risk models and decision engines.
• Stay informed on regulatory and compliance requirements related to data usage in financial services (e.g., Fair Lending, ECOA, GLBA) and align analytics practices accordingly.

Senior Data Analyst

Backend Engineer

• Back End Focused - Design, develop, and maintain scalable and high-performing web applications using modern technologies and frameworks.
• Collaborate with cross-functional teams to gather and analyze user requirements and translate them into technical specifications.
• Develop and implement front-end user interfaces and intuitive user experiences.
• Write clean, secure, and efficient code to ensure high-quality software development.
• Conduct thorough testing and debugging to ensure software functionality and reliability.
• Participate in code reviews and provide constructive feedback to improve code quality and maintainability.
• Keep up to date with industry trends and emerging technologies to continuously enhance the software development process.
• Completes all technical tasks assigned in each sprint
• Understands and improves all code bases currently under development
• Keep products up to date with new technology
• Assist in product releases, revisions, patches and code reviews
• Support and troubleshooting issues with existing code
• Collaborate closely with other teams within the organization
• Researches new technology and best solutions for each problem
• Be transparent in sprint planning/retrospectives

Senior Back End / Full Stack Software Engineer

Data Engineer

• Define end-to-end data architecture (lake/lakehouse/warehouse, batch/streaming, CDC, metadata).
• Set standards for schemas, contracts, orchestration, storage layers, and semantic/metrics models.
• Publish roadmaps, ADRs/RFCs, and “north star” target states; guide build vs. buy decisions.
• Design and build scalable, observable ELT/ETL and event pipelines.
• Establish ingestion patterns (CDC, file, API, message bus) and schema-evolution policies.
• Provide self-service tooling for analysts/scientists (dbt, notebooks, catalogs, feature stores).
• Ensure workflow reliability (idempotency, retries, backfills, SLAs).
• Define dataset SLAs/SLOs, freshness, lineage, and data certification tiers.
• Enforce contracts and validation tests; deploy anomaly detection and incident runbooks.
• Partner with governance on cataloging, PII handling, retention, and access policies.
• Lead capacity planning, partitioning/clustering, and query optimization.
• Introduce SRE-style practices for data (error budgets, postmortems).
• Drive FinOps for storage/compute; monitor and reduce cost per TB/query/job.
• Implement encryption, tokenization, and row/column-level security; manage secrets and audits.
• Align with SOC 2 and privacy regulations (e.g., GDPR/CCPA; HIPAA if applicable).
• Deliver versioned, documented datasets/features for BI and ML.
• Operationalize training/serving data flows, drift signals, and feature-store governance.
• Build and maintain the semantic layer and metrics consistency for experimentation/BI.
• Provide technical leadership across squads; mentor senior/staff engineers.
• Run design reviews and drive consensus on complex trade-offs.
• Translate business goals into data products with product/analytics leaders.

Principal Data Engineer

Business Development Rep

• Research and identify potential clients to generate new business opportunities.
• Conduct outbound prospecting activities, including cold calls, emails, and social media outreach, to engage with potential clients.
• Qualify leads by conducting needs analysis and evaluating their fit for Worth AI's products and services.
• Effectively communicate Worth AI's value proposition and offerings to potential clients.
• Schedule meetings and demos with qualified leads for the sales team.
• Maintain accurate and up-to-date records of lead interactions and status in CRM software.
• Collaborate with the sales and marketing teams to develop and execute strategies to drive lead generation and conversion.
• Participate in sales meetings and training sessions to enhance product knowledge and sales skills.
• Stay informed about industry trends and competitive landscape to effectively position Worth AI in the market.

Senior Data Scientist

Technical Support Engineer

Senior Data Analyst

Senior Back End / Full Stack Software Engineer

Principal Data Engineer

Sales Development Representative – SDR/BDR