Auditor

• Performing physical and remote audits of insured’s business
• Interviews, investigates, collects, and records information to be used in a written report that is provided to the insurance carrier

Insurance Auditor

AI Engineer

• Design, build, and ship production-grade Generative and Agentic AI applications and services for internal and external users
• Develop high-quality backend services in Python, with strong software engineering rigor around testing, performance, and maintainability
• Champion reusability and abstraction in everything you build by designing and building modular, well-abstracted components and libraries
• Build multi-agent systems using frameworks such as LangChain, LangGraph, Claude Agent SDK and Google ADK
• Integrate with leading LLM and foundation model APIs, including Azure OpenAI, Google Vertex AI, and AWS Bedrock
• Design and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking strategies, embeddings, vector search, and re-ranking
• Build clean, well-tested RESTful and/or gRPC APIs with a strong focus on reliability, security, and performance
• Implement observability, tracing, evaluation, guardrails for Generative and Agentic AI applications
• Deploy and operate services on major cloud providers (e.g., GCP, AWS, and Azure) leveraging managed services
• Contribute to platform architecture decisions and engineering best practices
• Take applications from prototype through production deployment, hardening, and ongoing operation
• Mentor and coach junior and mid-level engineers through code reviews, architecture discussions, and pair programming
• Foster a culture of engineering excellence, knowledge sharing, and continuous improvement
• Participate in technical design reviews and contribute to the professional growth of team members

Junior Gen AI Engineer

Artificial Intelligence

• Own end-to-end delivery of AI/ML and GenAI programs across multiple client engagements
• Drive execution across solution design, development, deployment, and productionization
• Ensure alignment with business objectives, SLAs, and delivery KPIs
• Work directly with enterprise clients to understand business problems and translate into AI solutions
• Act as a trusted advisor, influencing client strategy and AI transformation initiatives
• Operate in on-site / embedded engagement models, ensuring adoption and impact
• Lead design and deployment of AI/ML models, LLM-based solutions, and agentic workflows
• Build and mentor high-performing AI delivery teams
• Identify opportunities for AI-driven transformation use cases
• Lead by example with hands-on problem-solving and technical guidance

AI Delivery Lead

Accounts Receivable

• Carry out activities to support the Accounts Receivable cycle and subprocesses.
• The role involves calling customers for payments, payment processing, credit notes, write offs, reconciliations and reporting.
• Required interact with customers and agree before processing invoices
• Resolve all customer queries and requests coming via e-mails /tickets within the agreed SLA
• Perform account reconciliation between data from different systems
• Maintain exception logs for process related exception as and when they occur for knowledge retention
• Provide audit support where required
• Prepare reports as per requirements

Account Receivable Expert, French

QA Engineer

• Manage individual project priorities, deadlines, and deliverables.
• Design, develop, and execute performance test scripts/scenarios using Apache JMeter.
• Create workload models and execute load, stress, spike, endurance, Volume and scalability testing.
• Analyze latency and timeout root causes and provide recommendations for fixes.
• Analyze application performance bottlenecks and provide recommendations for optimization.
• Perform API performance testing to validate reliability, response times, and throughput of web services.
• Validate performance of ETL workflows using Informatica, including large-volume data processing and batch execution behavior.
• Design and execute performance test plans for applications hosted on Azure, Microsoft power Apps and other RPA tools.
• Monitor system/application performance using logs, dashboards, and available monitoring tools during execution.
• Communicate effectively with clients to gather non-functional requirements, provide updates, and address concerns.

QA Engineer – Manual and Performance Testing

Business Intelligence Developer

• Develop visual reports, dashboards and KPI scorecards using Power BI desktop
• Connect Power BI to different data sources, import data and transform data for Business Intelligence
• Proficient in creating complex DAX queries and bookmarks
• Implement row level security on data and have an understanding of application security layer models in Power BI
• Develop tabular/multidimensional models that are compatible with warehouse standards using M-Query
• Adept in developing, publishing and scheduling Power BI reports as per the business requirements
• Configure MS Azure resources to facilitate analysis process

Power BI Developer

Backend Engineer

Compliance

• Provide executive leadership and drive organizational growth through strategic initiatives.
• Set company vision, manage executive team, oversee major projects, and represent the organization externally.

Senior Executive – Compliance, Line Compliance

Data Engineer

• Develop and optimize ETL processes to support data integration and transformation requirements.
• Collaborate with business and technical teams to gather, analyze, and translate requirements into data solutions.
• Support business intelligence and analytics initiatives by ensuring data availability, quality, and consistency.
• Ensure solutions align with enterprise architecture standards, security requirements, and best practices.
• Conduct risk assessments and identify opportunities to improve data management processes.

Data Architect

Executive Assistant

• Lead the development and execution of financial risk and fraud strategies supporting key business initiatives and rapidly evolving risk environments
• Provide strategic oversight during high-severity and time-sensitive risk incidents, driving coordinated response and mitigation actions
• Leverage advanced analytics, statistical modelling, and deep domain expertise to design scalable risk frameworks using large-scale transactional and account-level data
• Own and optimize the end-to-end risk strategy and policy lifecycle: opportunity identification, strategy design, experimentation, deployment, governance, monitoring, and continuous improvement
• Drive portfolio-level risk management strategies across underwriting, fraud, credit, and money movement products while balancing risk, growth, and customer experience objectives
• Partner with senior stakeholders across Data Science, Risk Operations, Product, Engineering, Finance, Compliance, and Analytics teams to influence strategic decisions and business outcomes
• Lead segmentation strategy development, portfolio analytics, and performance deep dives to identify emerging risks and growth opportunities
• Design and refine underwriting frameworks, credit limits, eligibility policies, and customer risk segmentation strategies
• Establish scalable monitoring frameworks and governance processes to proactively manage portfolio trends, concentration risks, and segment-level performance
• Drive hypothesis-led innovation and experimentation to improve approval rates, reduce losses, and enhance operational efficiency
• Mentor and guide junior analysts and strategy team members, fostering analytical excellence and strategic thinking across the organization
• Communicate complex analytical insights and strategic recommendations effectively to executive leadership and cross-functional stakeholders

Senior Assistant Vice President – Credit Risk Strategy

• Lead script-level repointing across 593 downstream scripts (PySpark, BTEQ, Shell, SQL, IICS, SSIS) and 154 Databricks MLOps scripts from Teradata/SQL Server/Minio to Snowflake.
• Execute SQL syntax conversion for Teradata BTEQ scripts to Snowflake-compatible SQL, leveraging utility frameworks provided by the SI Partner (Infosys).
• Drive Airflow variable and connection updates across all migrated workflows, ensuring pipelines point to Snowflake endpoints post-cutover.
• Manage the script modification and change management process, coordinating production-to-parallel sync within the required 1-business-day SLA.
• Own the deployment and sign-off process for each migration wave, maintaining runbooks and go/no-go checklists per domain group.
• Own the parallel run and reconciliation cycle — execute data validation against Teradata source and Snowflake target, targeting sign-off within 2–3 reconciliation iterations per workflow.
• Serve as the EXL technical point of contact with the EBI client team for the repointing workstream — attending daily syncs, steering calls, and design reviews.

Lead Data Engineer – Snowflake

• Schedule and conduct premium audits with insured clients.
• Collect and review required documentation in compliance with client requirements.
• Prepare accurate audit reports according to company standards.
• Communicate effectively with insureds and internal stakeholders.
• Manage workload independently while meeting deadlines and quality standards.

Auditor II

• The Manager of Accounting & Tax will be responsible for overseeing daily accounting activities.
• Ensuring compliance with tax regulations, and assisting in the preparation of accurate and timely financial statements & tax filings.
• This role will work closely with senior management, external auditors, to ensure compliance with financial and tax reporting standards.
• The position requires strong technical accounting and tax knowledge, attention to detail, and the ability to manage multiple tasks in a fast-paced environment.
• Assists in the documentation process & preparation of SOPs.

Tax Manager

Data Analyst

• Define and mature the enterprise data governance strategy, roadmap, and operating model for P&C insurance data domains (Claims and Legal).
• Establish data ownership, data stewardship, governance councils, and decision forums across business and technology.
• Drive governance adoption aligned with business outcomes such as underwriting accuracy, claims efficiency, regulatory reporting, and analytics enablement.
• IDMC implementation and configuration including: Business Glossary and Data Dictionary, Data Catalog and Metadata Management, Data Lineage (technical and business).
• Partner with engineering teams to integrate Collibra with cloud platforms, data lakes, analytics tools, and core insurance systems.
• Manage IDMC environments (Dev/Test/Prod) and promote best practices.
• Ensure consistent documentation of critical data elements (CDEs) across P&C domains.
• Enable end‑to‑end data lineage from core systems (Policy Admin, Claims, Billing) to downstream analytics and reporting platforms.
• Improve data discoverability and self‑service analytics through standardized metadata and taxonomy.
• Define and monitor data quality KPIs (accuracy, completeness, consistency, timeliness).
• Establish governance processes for data quality issue identification, triage, remediation, and tracking.
• Work with IT and analytics teams to embed data quality controls into data pipelines and reporting workflows.
• Support data governance requirements aligned with state insurance regulations, privacy laws, and internal risk controls.
• Enable classification and governance of regulated and sensitive data used in underwriting, claims, and financial reporting.
• Partner with Legal, Compliance, and Risk teams to ensure audit‑ready data practices

Senior Data Analyst, Data Governance, Data Quality

• Design and implement scalable enterprise data architectures using Databricks Lakehouse platform
• Configure and manage Databricks workspaces, clusters, access controls, and governance
• Implement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics
• Set up and manage Lakehouse Federation and data connectors for multi-source integration
• Develop logical and physical data models for structured and semi-structured datasets
• Ensure data quality, security, scalability, and performance optimization
• Develop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows
• Build reusable data ingestion frameworks for batch and streaming workloads
• Optimize Spark jobs for performance, cost efficiency, and reliability
• Integrate data from relational and NoSQL databases, cloud platforms, and external systems
• Automate deployment and monitoring of ETL workflows
• Work with Azure and AWS cloud services to deploy and manage data solutions
• Configure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server
• Support CI/CD, infrastructure automation, and environment management
• Collaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders