Data Engineer at I&M Bank

The Digital factory will work under a special function hived off from the day to day operations and will collaborate with different functions of the Bank to deliver solutions that are customer centric in design and that will radically simplify business requirements and scale fast to full utilization using a clean sheet approach to deliver the desired value.

REF: DE /6/2018

JOB SUMMARY:

The role holder will be responsible for collecting, stitching together and analyzing data to enable insights (e.g., operational insights)

KEY ACCOUNTABILITIES

The Incumbent will report to the Digital Factory Manager or any other official as may be designated and will be responsible for:

• Thinking in terms of databases, structured and unstructured data and integrating data in clean accurate ways. Also building reports and dashboards using Spotfire and Tableau
• Acting as a liaison between Analytics and IT teams
• Assisting data scientists to transform their algorithms into usable and performing code
• Developing data and information structure
• Interacting with data scientists and translators to understand how data needs to be presented

COMPETENCIES REQUIREMENT:

Qualification

• BS/BA Degree (MS preferred) preferably in Computer Science, Statistics, Math or equivalent combination of education and experience
• SQL skills and experience in working with Hadoop, Hive, Map Reduce, Teradata, QSTK, R, Python, C# and, Java
• Solid business and collaboration skills, and responsive to service needs and operational demands

Experience

• 5+ years of experience with data analysis and preparation, including considerable experience with very large data sets and unstructured data
• Strong experience in database development & data model design

Knowledge

• Deep knowledge of machine learning, statistics, optimization or related field
• Experience with R, Python, Matlab is required, programming in C, C++, Java
• Knowledge of computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)
• Advanced knowledge of statistical techniques, data mining, machine learning (regression, decision trees, clustering, random forests, generalized linear models, etc.)
• Attitude to thrive in a fun, fast-paced start-up like environment