... productivity - including AI-assisted coding, automated data validation, and GenAI-driven analysis workflows- Contribute to the development and testing of AI-powered product features, such as natural language interfaces, intelligent data exploration, or automated reporting- Prototype and evaluate new AI/ML approaches for ...
Job Description – Data Engineer Experience: 5–7 Years Role: Sr. Data Engineer Department: Data Engineering / Product Engineering Role Overview We are looking for an experienced Data Engineer with 5–7 years of hands-on experience in ETL/ELT, database engineering, Big Data processing, and complex bi-directional data integrations ...
... factual accuracy, or comparing responses — when projects are available. While each project involves unique tasks, contributors may: - Carefully review provided data (text, images, or videos); - Label or classify content based on project guidelines; - Identify and flag factually incorrect, sensitive, inappropriate, or unclear ...
... production-ready code and perform data analysis with Python and SQL Create workflows for model development and apply feature engineering methods Use Azure AI Search to make data and models easier to consume for business needs Coordinate with developers and project managers using GitLab and Jira Refine data pipelines and tune model performance ...
Role Overview : As a commercially savvy Lead Data Scientist, you will lead your team on client briefs whilst collaborating closely with consultants and Trade Partner stakeholders. You'll bring fresh ideas and innovative thinking to push the boundaries of what's possible with consumer analytics. You will drive AI excellence ...
... artefacts that exploit data models to understand data and data integrations. This may include modelling data flows, developing CRUD matrices to understand master data, and the use of process models to illustrate master data flows.- Analyze complex datasets to identify trends, anomalies, data gaps, and business insights that ...
... workflows, and structured output pipelines for LLM applications. Fine-tune, evaluate, and optimize LLM-powered applications for accuracy, latency, and cost. Implement data preprocessing, feature engineering, and ML model training workflows. Work with structured and unstructured datasets to solve business problems. Collaborate with ...
... hands-on professional experience Education: BE/B.Tech/ME/M.Tech/MCA/MSc IT Primary Skills (must have): Strong Azure or AWS knowledge Strong working knowledge on Data Science, Artificial Intelligence, Machine Learning Secondary Skills (good to have): SQL, Python Professional Attributes: Strong analytical and problem-solving ...
We are looking for a hands-on Data Scientist to join the Commodities At Sea (CAS) team. The role combines large-scale data processing, data wrangling and analytical problem-solving with the development of reliable, production-ready data products for maritime and commodity-flow analytics. The successful candidate will work ...
... Experience with MDM / Data Governance platforms such as Syniti, SAP MDG, Informatica MDM, or any home grown Strong understanding of data governance operating models, data ownership, data stewardship, workflow approvals, data quality rules, metadata, and data lifecycle management. Experience in data profiling, cleansing, harmonization, ...
... proficiency in SQL and Python for data processing and pipeline development. Data Platforms: Hands-on experience with Snowflake, dbt, and modern cloud data warehouses. Data Modelling: Deep experience with dbt and modern data modelling practices. Data Platforms: Hands-on experience working with Snowflake or comparable cloud data warehouses ...
... Measurement Team that specializes in the ingestion, transformation, and storage of large-scale social and broadcast data. Working under the guidance of an experienced Data Engineers and Architects, you will gain hands-on experience designing and maintaining scalable, efficient data pipelines that support enterprise web applications, ...
... learning, artificial intelligence, and data-driven decision support across enterprise processes. The successful candidate will partner with business stakeholders, data engineers, software developers, and digital transformation teams to identify opportunities, design AI-powered solutions, and deploy scalable models into production. ...
... their investments, trade seamlessly, and access financial tools tailored to their goals. We are working to build personalized financial journeys for our clients, powered by new-age tech, AI, Machine Learning and Data Science. Be part of a team that's scaling sustainably, thinking big, and building for the next billion. Tech ...
Role Purpose This role is responsible for driving enterprise-wide data engineering strategy. It ensures the design, implementation, and continuous improvement of data pipelines, scalable and reusable frameworks, and implement data governance and data quality engines. The position enables trusted, governed data across systems, ...
... least one certification • Databricks Certified Data Engineer Associate OR Databricks Certified Data Engineer Professional Additional Certifications (Preferred) - Databricks Certified Associate Developer for Apache Spark - Cloud platform certifications (Azure Data Engineer Associate, AWS Certified Data Analytics, or Google Cloud ...
... distributed architectures, and modern data engineering https://jobeax.com/link/TtkK7BHPbancvnFq Responsibilities:- Design, develop, and maintain scalable ETL/ELT data pipelines.- Build and manage distributed and event-driven architectures for large-scale data processing.- Develop backend services and data infrastructure using ...
... using Python and PySpark to ingest data from files, APIs, RDBMS, NoSQL, and message queues into AWS data stores Develop and optimize PySpark jobs for large-scale data processing, transformation, and aggregation on AWS EMR or Databricks Build and manage AWS-native data workflows using S3, Glue, Lambda, Redshift, and Step Functions; ...
Position: Data Scientist Experience: 3 – 4 Years We are looking for a Data Scientist to help us see those patterns earlier: which investors need a nudge, which portfolios are drifting off-plan, and which programs are actually moving the needle. Investment and portfolio analytics- build models that surface portfolio drift, ...