... years of experience in data science, including hands-on development of AI/ML or optimization models and at least 2 years working with process event or behavioral data. - Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field. - Proven track record of building ...
... 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 ...
... document methodologies, and support junior geospatial analysts. - Promote best practices in model development and code quality. - Translate business problems into data science solutions and communicate results to stakeholders. Master’s/PhD in Remote Sensing, Geoinformatics, Agriculture Engineering, Earth Sciences, Environmental ...
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 ...
... 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 ...
... 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 ...
... 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 ...
... years of professional experience in data engineering, with a focus on data modelling and transformation. Programming: Strong 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 ...
... passionate about data and infrastructure, comfortable making and communicating technical decisions, and interested in continuously improving our architecture, engineering practices, and technology stack. Provide technical leadership for the Data Engineering team, helping establish technical direction, engineering standards, ...
... 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 ...
Role Purpose This role is responsible for driving enterprise-wide data engineering strategy. It ensures the design, implementation, and continuous improvement of data pipelines, scalable and reusable frameworks, and implement data governance and data quality engines. The position enables trusted, governed data across systems, ...
... junior data engineers on PySpark and Databricks technologies - Document technical solutions and maintain comprehensive documentation Essential Technical Skills - Data Engineering: Strong foundation in data engineering principles, ETL/ELT processes, and data pipeline design patterns - PySpark: Proven hands-on experience developing ...
... distributed architectures, and modern data engineering https://jobeax.com/link/TtkK7BHPbancvnFq Responsibilities:- Design, develop, and maintain scalable ETL/ELT data pipelines.- Build and manage distributed and event-driven architectures for large-scale data processing.- Develop backend services and data infrastructure using ...
... expertise in Python, PySpark, and AWS to design, build, and operate scalable data pipelines for analytics and operational workloads. You will own end-to-end data engineering — from ingestion to delivery — across batch and near-real-time patterns, with a focus on pipeline reliability, data quality, and cloud-native engineering. ...
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, ...
... 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 ...