Data Engineer - Machine Learning

Introduction
At IBM work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so lets talk.

Your Role and Responsibilities

As an entry-level Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You’ll contribute to data gathering storage and both batch and real-time processing.

Collaborating closely with diverse teams you’ll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer you’ll tackle obstacles related to database integration and untangle complex unstructured data sets.

In this role your responsibilities may include:

• Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data incorporating a variety of statistical and machine learning techniques
• Designing and implementing various enterprise seach applications such as Elasticsearch and Splunk for client requirements
• Work in an Agile collaborative environment partnering with other scientists engineers consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors.
• Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner developing predictive or prescriptive models and evaluating modeling results

Required Technical and Professional Expertise

• Ability to incorporate a variety of statistical and machine learning techniques
• Basic understanding of Cloud (AWSAzure etc)
• Ability to use programming languages like Java Python Scala etc. to build pipelines to extract and transform data from a repository to a data consumer
• Ability to use Extract Transform and Load (ETL) tools and/or data integration or federation tools to prepare and transform data as needed.
• Ability to use leading edge tools such as Linux SQL Python Spark Hadoop and Java

Preferred Technical and Professional Expertise
N/A