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Data Scientist: Artificial Intelligence
IBM
Software Engineering, Data Science
Multiple locations
Posted on Dec 18, 2024
Introduction
As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Your Role and Responsibilities
As a Data Scientist at IBM, you will help transform our clients’ data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it’s investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.
Your Role and Responsibilities
As a Consultant you will serve as a client-facing practitioner who sells, leads and implements expert services utilizing the breadth of IBM’s offerings and technologies. A successful Consultant is regarded by clients as a trusted business advisor who collaborates to provide innovative solutions used to solve the most challenging business problems
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Required Technical and Professional Expertise
- 8 + years of validated experience in Cyber Security/Fraud Detection, MachineLearning and Data Science.
- Working experience with Python, Pyspark, Machine learning (Supervised &Unsupervised) and deep learning frameworks like Scikit-learn, PyTorchExperience in mining features from Clickstream data, CDN and various big datasources to support anomaly detection/fraud related use cases
- Experience applying data science techniques to the cyber security and bot/fraudproblem set, and domains like graph models, GNN, GAN, Natural LanguageProcessing (NLP), Bayesian models, UBA, GenerativeAl and a variety of neuralnetwork approaches.
- Hands on experience with MLOps frameworks and AWS such as Airflow. Sagemaker Model Serving (Real time/batch) and distributed trainingProven ability in interpreting/implementing methods described in research papersand articles in machine learning, deep learning, mathematical modeling andrelated fields. Strong understanding of data and analytics, including experience with Big Data,real time and batch data processing. End to end ownership of the engineering cycle for Al/ML
Preferred Technical and Professional Expertise
- Bachelor’s or Master’s Degree, MBA is a plus
- English: Fluent both oral and written