... orchestration, OneLake concepts and Power BI semantic 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. ...
... coaching, performance management, career 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 ...
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 ...
... 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 ...
... interactive MI Dashboards using Power BI to provide actionable insights. This includes creating data models, developing complex DAX queries, and integrating various data sources to ensure comprehensive and real-time reporting. Data Analysis and Reporting: Perform in-depth analysis of large datasets to identify trends, patterns, ...
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 ...
... maintain scalable ETL/ELT pipelines for batch and near-real-time data processing. Build data integrations using REST APIs, SFTP, files, webhooks, and database-to-database interfaces . Develop and support bi-directional data integrations between applications, databases, and external enterprise systems. Implement data synchronization, ...
... and advanced analytics techniques, then fix the cause and embed uplifted evergreen controls to prevent future failures Develop proactive controls to reduce the time from data quality issue identification to resolution, improving client experience and driving operational efficiency through elimination of cost of poor quality ...
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 ...
... systems (e.g., SAP, Salesforce, ServiceNow) into structured, analysis-ready pipelines for process-mining and machine-learning applications. Collaborate with senior data scientists, data engineers, and software developers to embed models into Shell's process-mining platform for scalable, real-time analytics. Develop algorithms ...
... content, evaluating 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, ...
We are building a team around a Senior Data Scientist role focused on measurable AI outcomes through statistical analysis, machine learning, and NLP. You will work across the full lifecycle, from preparing data to deploying models, coordinating closely with multiple stakeholders. Responsibilities Deliver AI solutions such ...
... Database interaction to query cloud-based data warehouses. Cloud services such as S3 and AWS Lambda for infrastructure management. Familiarity with cloud-native databases such as Snowflake, Postgres, Redshift. Code quality and management using version control and collaborative workflows. Full lifecycle experience — you've ...
... analytical methodologies, and scale AI impact through strategic application of tools and technologies- Build and lead high-performing teams : Lead a team of 6 - 10 data scientists with full accountability for performance management, capability development and career growth- Deliver high-quality analytical solutions : Lead team ...
... 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 ...
... 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)
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, ...