Data Scientist – FinOps

Key Skills

Aartificial intelligence, Algorithms, AWS, Data Modeling, Data science techniques, Data structuring, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Numerical Computing, Pandas, PySpark, Python Programming, Scikit-learn, Statistics

Job Description

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

Want to help the Apptio, an IBM company derive business value through the adoption of Artificial Intelligence (AI) You will get to work with an innovative company, with great teammates, and have a lot of fun helping our customers. A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing data driven solutions

Responsibilities

Assist customers by being able to deliver a project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring as complete product and retraining to deliver business impact to the organization.

Required Technical and Professional Expertise

• Bachelor’s degree in a highly quantitative field (Computer Science, Machine Learning, Statistics, Mathematics, etc.) or equivalent professional
• 1 to 3 years of industry experience in predictive and prescriptive modeling, data science, and analysis
• Experience in Machine Learning, Deep Learning, Statistical Models, NLP, Time Series, Algorithms
• Data Scientist role building, deploying and maintaining ML model
• Experience writing production level code in Python, (Pandas, Scikit-learn, or PySpark)
• Experience in ML Engineering developing data science products
• Experience in text data, numerical, structured, unstructured data types

Preferred Technical and Professional Expertise

• Proficiency in AWS and other cloud technologies
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment