... analytical solutions. - Experience working closely with Finance, Risk, or business stakeholders is highly desirable. - Experience in FinTech, Banking, Financial Services, or related industries will be a strong advantage. - Strong understanding of dashboard design, data storytelling, visual hierarchy, and analytical communication. ...
... Strong knowledge of Object-Oriented Programming (OOP) and experience creating custom Python packages for serverless applications. - Hands-on experience with AWS services including Lambda, EC2, EMR, S3, Athena, Batch, Textract, and Comprehend. - Work seamlessly across Data Science, Engineering, Product, DevOps, and Data Engineering ...
... Develop AI agents using Agentic AI frameworks such as LangGraph, LangChain, CrewAI, or similar technologies. Integrate AI agents with enterprise APIs, tools, databases, and external services. Develop prompts, tool-calling workflows, and structured output pipelines for LLM applications. Fine-tune, evaluate, and optimize ...
... Databricks, including development, optimization, and management of large-scale data processing and analytics workload- Must have an understanding of streaming data pipelines for near real-time analytics- Hands-on experience and good understanding of AWS services for data engineering, including AWS Glue, Lambda, Step Functions, ...
... media, or similar industries. Strong problem-solving skills with a focus on agile and iterative product development, enabling innovative solutions to complex data challenges. Knowledge of web services and cloud platforms (e.g., AWS, Redshift, Azure) for scalable data operation and integration. Ability to translate complex ...
... your mark by leading global asset pricing controls that help protect clients and the firm, while growing your career in a collaborative team. As a Reference Data Analyst within Instrument, Pricing & Common Reference Data, you deliver daily global asset pricing services and ensure data integrity across multiple business ...
Position: Senior Data Engineer Location: Pune Job Responsibilities Design, develop, and maintain scalable data pipelines using AWS services. Design and implement scalable, secure, and resilient MLOps architecture across cloud and on-prem environments Define best practices for model lifecycle management, including versioning, ...
Quantium is a world leader in data science and artificial intelligence. Established in Australia in 2002, Quantium is a global team of more than 1,200 people across 14 locations with a unique blend of capabilities across product and consulting services to help businesses unlock value from data and https://jobeax.com/link/UvUertRTRUIC87ia ...
... Develop complex queries using Cypher Query Language (CypherQL). Implement Graph Data Modeling techniques for relationship-driven datasets. Work with PostgreSQL databases for structured data management and optimization. Develop APIs and backend services using FastAPI. Integrate multiple data sources and ensure data consistency ...
... Power BI and/or Tableau Solid understanding of data modeling, data cleaning, and transformation techniques Experience working with structured and unstructured datasets Familiarity with statistical analysis and data visualization best practices Experience in an analytics services or consulting environment Exposure to cloud ...
... processes. - Experience translating business requirements into features, user stories, data requirements, and acceptance criteria. - Hands-on experience with data validation, reconciliation, source-to-target mapping, UAT, and defect management. - Understanding of data flows, cloud platforms, data repositories, and reporting/visualization ...
... structures. Exposure to AWS services relevant to data platforms (S3, Glue, Lambda, IAM, Secrets Manager) and Infrastructure as Code with Terraform. Experience with data cataloging, lineage, and governance tooling (Atlan, Collibra, Alation, Snowflake Horizon, OpenMetadata). Experience supporting business-facing data stewardship ...
... corporate governance data accurate, secure, and easy to use. As a Professional Services Data Entry Specialist, you turn complex client records into clean, reliable datasets and documents that board members, legal, risk, and compliance teams rely on to make decisions. In this role, you'll work hands-on with governance data, migrate ...
... model monitoring approaches - Strong understanding of data engineering and model integration patterns, including working with SQL, batch pipelines, streaming data, APIs, and application services - Familiarity with observability and operational tooling such as Azure Monitor, Application Insights, MLflow tracking, Datadog, ...
... focus on Generative AI https://jobeax.com/link/yEDVIXaeb96i6mjc : - Develop, implement and deploy ML & GenAI use cases.- Work hands-on with large volumes of data, including extraction, cleaning and analysis.- Work on Prompting, RAG, Agents and LLMs.- Leverage AI cloud services including AWS, Azure and GCP.- Work on NLP, ...
... Implement 'Data SLAs.' You will build the monitoring and alerting systems that notify the team of data drift or pipeline failures before the business notices. Data Productization: Work closely with the BI team and Data Scientists to prepare 'feature-ready' datasets. Performance Tuning: Deep-dive into SQL and Spark query ...
Big Data Processing: Design and manage scalable data pipelines to process massive datasets efficiently for model training and inference. Build, train, and fine-tune complex neural networks across text, audio, and visual modalities. Cloud Deployment: Architect and deploy models to cloud environments, leveraging distributed ...
... with minimal supervision - Prior experience in reporting, operations, analytics, or finance support roles is essential - Experience in international or shared services environments is desirable Performance Measures Accuracy and integrity of all data outputs - Enjoy working with data - Want to build a long-term career in finance, ...
Kroll is hiring a Senior Data Scientist to join its Enterprise Data Group. This role is designed for an experienced practitioner who can lead end-to-end ML initiatives, mentor junior team members, and partner with business and engineering stakeholders to translate complex problems into production-grade data science solutions. ...
... with cloud-based data platforms and services, including AWS, Google Cloud, or Microsoft Azure. - Familiarity with MLOps, machine learning infrastructure, or data science workflows. - Experience building data systems that support analytics, machine learning, or other high-volume data applications. Who Should Apply This ...