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 ...
... Data Factory or equivalent. Data Handling: Expertise in data engineering, including data cleaning, transformation, and preparation for analysis. Knowledge of data modelling, database design, and data architecture principles. Data Quality: Proven experience in data quality management, including data cleansing, validation, ...
Role Overview :The Senior Data Scientist, Product Analytics is a hands-on technical contributor and task manager within a cross-functional product team. This role sits at the intersection of deep technical execution and emerging AI https://jobeax.com/link/f9LyLs7glaUomOJP And Qualifications :- 5 - 7 years of experience ...
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 ...
... Hands-on experience with data lineage tools and techniques, including graph databases and metadata management platforms. Knowledge of data governance frameworks, data quality dimensions, and regulatory requirements (e.g., BCBS 239, GDPR) Experience with AI/ML technologies and their application to data management challenges ...
Role Overview We are looking for a Senior Data Analyst to work on a broad range of data analytics, data visualization, and business intelligence initiatives across multiple industries. The role requires strong analytical skills, frequent client interaction, and the ability to translate business problems into effective analytical ...
... learning, statistical modeling, and process-mining algorithms to large, multi-source enterprise datasets. - Strong programming proficiency in Python, SQL, and data-modeling techniques for event data. - Experience in process data model design, development, and deployment, including creation of reusable data schemas and pipelines ...
... 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 ...
... and modern orchestration — empowering the organization to make reliable, governed, data-driven decisions. Data Platform Architecture: Design and own end-to-end data pipeline architecture — ETL/ELT, orchestration, and data modeling — across cloud-native platforms (Azure Databricks, Azure Data Factory, and/or Snowflake). Lakehouse ...
... 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 ...
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 ...
... 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 Product Managers, Software Engineers, and Subject Matter Experts to deliver AI-driven features. Monitor model ...
... 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 ...
... 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 ...
... and commodity-flow analytics. The successful candidate will work extensively with Python and PySpark, use R where appropriate, and collaborate with product managers, industry analysts, data scientists and technology partners. The role also contributes to cloud and DevOps activities across AWS, Docker and Terraform when ...
Job Title Master Data Management Lead ( Sr Manager – IT ) VP-IT / Global COE Head The Master Data Management Lead will be part of the Global Center of Excellence (COE) for CONMED, which will be operational from India. This role is crucial in building, governing, and operating enterprise master data capabilities across SAP ...
... 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 ...