... 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 ...
... trade-offs and limitations clearly to technical and non-technical audiences. 3-6 years of relevant experience in data science, data engineering, analytics engineering or a closely related role, including at least 3 years of hands-on experience with Python and Spark/PySpark. - Strong practical knowledge of Python data tooling ...
... Information Technology, Data Management, Engineering, Business Administration, Supply Chain, Finance, or related field. Certification in SAP, SAP MDG, Syniti, Data Governance, or equivalent preferred. Experience Must have 12–15+ years of overall experience in Data Management, ERP, SAP, Data Governance, Data Quality, or Enterprise ...
... opportunities, and business insights. Create dashboards, visualizations, and reports that communicate insights effectively to technical and non-technical stakeholders. Data Engineering & Solution Delivery Collaborate with data engineering teams to establish scalable data pipelines and AI-ready data platforms. Ensure data quality, ...
... 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 curation, feature engineering, model training, model tuning, and offline & online experimentation Strong programming skills with minimum 3-6 years of experience ...
... forecasting, and decision support. Skills You Can Develop: During the internship, you can gain practical exposure to: Data Analytics | Business Intelligence | Data Cleaning | Exploratory Data Analysis | Data Visualization | Dashboard Development | Business Analytics | Statistical Analysis | Data Interpretation | Reporting ...
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, ...
... including hands-on experience with prompt engineering, RAG, embeddings, and agentic workflows - Practical experience building LLM/GenAI applications — prompt engineering, RAG, fine-tuning, embeddings, vector databases, and evaluation - Solid grounding in the full ML lifecycle: data validation, feature engineering, model design, ...
... experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies. Provide technical ...
... Capital, Matrix Partners, Ventureast, and Helion https://jobeax.com/link/YG6VptVu4UkNxzCB Omni-Channel Marketing Platforms for B2C Enterprises 2023. As part of the Data Science/Engineering team at MoEngage, here are some things you can expect: Work with A players (some of the best talents in the country), and expedite your learning ...
... deploy real-time decisioning rules and ML systems to detect synthetic fraud, digital identity theft, account takeovers, and transactional fraud. - Feature Engineering: Mine complex, large-scale, and alternative data streams (bank transactional data, logs, credit bureau reports, structured/unstructured digital signals) ...
... experimentation, and prompt design; collaborating with Product and Software Engineering to embed AI/ML into user-facing applications; engaging with DevOps/Platform Engineering on environment setup, CI/CD, monitoring, and reliability; and working with Data Engineering on pipeline design and ingestion strategies. Provide technical ...
... reporting, and metadata coverage.- Collaborate across business, IT, legal, and compliance teams for role https://jobeax.com/link/D9UR6EbHufGvIjFa Candidate :- Strong Data Governance Lead Profile with deep Microsoft Purview and enterprise governance expertise.- 7+ years of experience in data governance and data management with at ...
... applications, or hybrid modeling approaches (physics-informed ML, combining domain knowledge with ML) - Familiarity with Agile development methodologies - Knowledge of data engineering, data warehousing, and SQL - Experience using data science techniques to solve real-world problems across multiple business domains and communicate ...
... 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 ...