... 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 . The candidate should have strong SQL and database expertise, experience working with large datasets, ...
... skills 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 ...
... 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 for process analytics. - Experience integrating ML models with process-mining platforms such as Celonis EMS or open-source frameworks (PM4Py, ...
... 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 ...
... data transformations. Reporting Enablement: Ensure the platform reliably feeds downstream BI tools (Power BI or similar) with clean, curated, analytics-ready data. Performance Optimization: Analyze and optimize Spark/pipeline workloads for performance, scalability, and reliability. Data Governance: Implement RBAC, data ...
... 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 ...
... 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 ...
... knowledge on Data Science, Artificial Intelligence, Machine Learning Secondary Skills (good to have): SQL, Python Professional Attributes: Strong analytical and problem-solving abilities Ownership mindset with a focus on quality and scalability Additional Details • Work Mode & Location: Full-time, Work from Client (Mumbai)
... 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 ...
... research and data-science stakeholders make informed decisions. AI Workflow Automation Identify high-value opportunities to automate repetitive data and research workflows using generative AI, machine learning and rules-based orchestration. Design and implement AI-assisted workflows such as document and data extraction, semantic ...
... 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 ...
... part of our Partnership Intelligence 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 ...
... unstructured data. Develop and optimize Generative AI solutions, including LLM-based applications, RAG architectures, AI assistants, and intelligent automation workflows. Evaluate, monitor, and continuously improve model performance and accuracy. Data Science & Analytics Perform exploratory data analysis to identify trends, ...
... comprehensive benefits package includes health insurance, wellness programs, learning & development opportunities, and more. Job Title: Data Scientist 2 Understand data landscape Perform ad-hoc analysis and present results in a clear manner Work on the full lifecycle of machine learning development including sourcing, dataset ...
... AWS, and GCP. Develop modular, reusable data engineering frameworks for ingestion, transformation, and orchestration. Build Spark, SQL, and Python workflows in Databricks. Optimize compute, storage, and pipeline performance for cost efficiency. Data Quality, Governance & Security Build custom data quality (DQ) frameworks ...