... 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 material. What we look for This opportunity is a good fit for candidates open to part-time, non-permanent projects. Ideally, contributors ...
... models, including Direct Lake where appropriate. - Experience with data warehouses, data lakes and Azure data services such as Azure Data Lake Storage and Azure Data Factory. - Strong knowledge of dimensional modelling, analytical structures and data-modelling trade-offs. - Experience implementing unit, integration, reconciliation ...
... databases. Review data for accuracy, completeness, and quality. Process large volumes of information with high attention to detail. Generate reports and perform basic data analysis using Excel. Coordinate with US-based teams to resolve data discrepancies. Maintain confidentiality and security of sensitive information. Meet daily ...
... development, and team engagement. Data Architecture: Deep understanding of modern data architecture patterns including Data Lakes, Data Warehouses, Lakehouses, and Data Mesh, combined with experience designing and delivering cloud-based data platforms. Cloud and Data Engineering: Strong experience with AWS and Snowflake, as well ...
... Data Scientist or Machine Learning Engineer with a portfolio of complex multimodal projects. Honeywell Technologies is a global, pure-play automation company with a legacy of innovating to help solve the world's most mission-critical challenges, enhancing the quality of life for people and communities around the world. ...
... Point - Ability to prioritize tasks, manage multiple responsibilities and ensure deadlines are met without compromising on quality - Basic data handling and Data interpretation skills - Should be comfortable with 24x7 rotational shifts - Ability to pull data from numerous databases (using Excel and other data management ...
... analytics solution design with minimal guidance - typically components with clear input/output requirements such as predictive models, allocation schemes, or data transformation pipelines- Design, develop, prototype, and test analytics algorithms, writing clear specifications for implementation by engineering teams where ...
... long-running query optimization. Work with large datasets and distributed processing frameworks; optimize data processing for scalability and performance. Implement data validation, quality checks, logging, auditing, and monitoring for critical pipelines. Troubleshoot production ETL, database, integration, and data-quality issues ...
... enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI-assisted outputs (e.g., model/design summaries or operational checklists) before use, escalating when uncertain and following data handling ...
Research and Development Business Unit: Finance Experience Level: Experienced Professionals The Commercial Data Science (CDS) team partners with Shell's business units to deliver data-driven solutions through deep process understanding and technical excellence. As a Data Scientist within the Digital Process Twin (DPT) portfolio, ...
... 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 material. What we look for This opportunity is a good fit for candidates open to part-time, non-permanent projects. Ideally, contributors ...
... 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 ...
... time-series modeling). - Integrate outputs with downstream systems (dashboards, APIs, ML models) to support digital agronomy and sustainability reporting. - Maintain data quality, document methodologies, and support junior geospatial analysts. - Promote best practices in model development and code quality. - Translate business ...
... 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 Engineering: Architect Medallion (Bronze/Silver/Gold) ...
... analytics environment with proven analytics and insights expertise at Lead Analyst level or equivalent- Technical proficiency : Strong expertise in BigQuery SQL and data visualisation tools- Leadership experience : Proven experience leading teams of analysts and managing analytical deliverables- People management : Experience ...
... through validation and quality checks.- Work with multiple IT roles including Data Analysts, Solution Architects, and Information Architects to embed the use of data models within both project and strategic activities.- Work with business data governance teams to embed the use of data models and associated definitions within ...
... 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 ...
... 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)
... problem-solving with the development of reliable, production-ready data products for maritime 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 ...
... improve stewardship productivity, reduce data defects, and enhance reporting confidence. technologies, SAP MDG capabilities, Syniti functionality, AI-enabled data quality, and industry best practices. Team building and mentorship: Build and mentor a high-performing MDM team including data stewards, analysts, functional ...