Added advantage with hands on experience on Databricks, Snowflake & Palantir. Candidate should know how to utilize Graphs Datasets (Neo4J or Knowledge graph Data sets) in “Data Science graphs use cases and Algorithms” (clustering, community detection, DFS, BFS, GNN and CNN and Deep Learning, etc.

Working knowledge and/or hands on fraud detection experience with card products, card processors, card networks, and one or more fraud rule systems such as Defense Edge, FDWC, Falcon Expert, Tsys Card Guard, Tsys Determinator, Broadcom 3DS, Token Administration, Visa Risk Manager.

As an IT Trainee/Intern, you'll be thrust into the forefront of technological innovation, working on projects that span software development, network security, and data analysis. This role offers the rare opportunity to collaborate with leading IT experts, gain hands-on experience with cutting-edge technologies, and contribute to projects that shape the future of technology.

Experience with at least one major data visualization/analytics tool (e.g., Tableau, PowerBI, QlikView, Alteryx), evidenced by hands-on usage, project work, etc. Create data science assets and automations using a combination of tools and languages including SQL, Python, R, Alteryx, Tableau, Microsoft Azure (Fabric, ML Studio, ADF, Synapse, PowerBI, etc.

Hands-on experience, development, and expert knowledge of Collibra or similar catalogue/data governance platforms in support of multiple domains. Is seen as a delivery-oriented operational Business partner able to support and develop products for data capability which deliver on pressing needs across data analytic science, program/business needs, technology, and process enablement.

Every team member is passionate about technology, data sciences, and hands-on coding with a focus on impactful results. Knowledge of big data, data science, generative AI, machine learning, and common Python libraries.

We seek a self-motivated individual with strong programming skills, hands-on experience with TensorFlow or PyTorch and python coding, and a passion for developing intuitive, well-architected, and maintainable software tools.

Nice to have: Experience in a sales support role, within Data Science, Machine Learning, or AI. Familiarity with leading data platforms like Databricks and Snowflake, and their basic services.

Our 11-week paid internship program gives interns hands-on experience working with various groups across multiple office locations within Comcast’s Central Division. Currently pursuing a major in Political Science, Public Relations, Communication, Journalism, or related fields.

Solid modeling foundation is a plus, including hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression, tree-based methods, neural nets, support vector machines, anomaly detection, and natural language processing.

Qualifications: Bachelor's degree in Information Systems, Computer Science, Data Analytics, Management Information Systems, Information Technology, or a related field; a Master's degree is a plus Practical experience in software development.

Hands on experience with Data Science tools and technologies on AWS with Python. Preferably 10+ years' experience having strong Data Analytical Skills with Hands-on Experience in Designing and Developing complex BI and Data Analytical Solutions.

Demonstrated, hands-on experience with data visualization tools, e.g. Looker and Tableau. Bachelor’s or Graduate degree, Field of Studies required: In a quantitative field or commesurat experience such at Statistics, Business Analytics, Data Science, Applied Math, Econometrics or Operations Research.

Hands-on experience with Databricks, Apache Spark, and cloud platforms such as AWS, Azure, or Google Cloud Platform. Adept coding skills in Python, Scala, or SQL and a strong foundation in data governance and security.

5+ years of hands-on experience in predictive modeling, analysis and machine learning. BS or MS degree in Computer Science, Mathematics, Statistics or another highly quantitative field.