Data Scientist job at Housing Finance Bank

Data Scientist job at Housing Finance Bank

JOB DETAILS:
Job Purpose
Responsible for collecting, analysing, and interpreting large amounts of data to identify ways to help Bank improve Strategic planning, operations, and systems and in turn transform customer experience delivery.

Key Result Areas
• Develop predictive and descriptive models using machine learning, advanced statistical, optimization, and big data techniques including multivariate, regression, decision trees/ classification, and time series
• Assist in identifying critical questions to be answered and contribute to developing analytics-driven solutions and KPIs to enable more effective decision making.
• Conduct analysis and data modeling to draw insights that drive critical decision-making and uncover patterns in customer uptake of bank solutions and other ICT indicators.
• Create various machine learning-based tools or processes within the Bank, such as recommendation engines or automated lead scoring systems.
• Interacting with business stakeholders across departments to define project requirements, test prototypes, and communicate results.
• Perform data mining and carry out statistical analysis on data collected from various departments and Bank systems.
• Research, evaluate, and recommend systems/equipment/ technologies based on departments’ needs for the data.
• Run reports to be utilized for strategic planning in the Bank.
• Utilize practices and tools for data extraction, queries, and data manipulation in accordance with business processes in the Banking industry.
• Work with the Bank’s integration platform to produce data for analytics, dashboard, and reports.
• Enhance data collection procedures to include information that is relevant for building analytic systems.
• Work with the ICT team to set up big data processing platforms and data pipelines for both batch and online data analysis.

Person Specifications
Education & Training
• Minimum qualification of bachelor’s degree in Computer Science, Information Systems, Information Technology, Software Engineering, Statistics, Mathematics or a similar field from a recognized university.

Skills & Experience
• Excellent understanding of machine learning techniques and algorithms for both supervised, unsupervised, and reinforcement learning.
• Experience with common data science tools such as Python, NumPy, MATLAB, R, or SAS.
• Experience with data visualization tools, such as D3.js, ggplot, Seaborn, etc.
• Ability to develop models on amazon web services or other cloud platforms using the above tools or frameworks such as TensorFlow is an added advantage.
• Business Behaviours
• Aggressive problem diagnosis and creative problem-solving skills
• Strong organizational skills to juggle multiple tasks within the constraints of timelines and budgets.
• Ability to work and thrive in a fast-paced environment, learn rapidly and master diverse software technologies and techniques.
• Interpersonal skills
• Excellent communication skills (verbal & written) and presentation skills.

Job application procedure

Interested candidates should submit their applications with a recent CV, copies of all academic transcripts, certificates and testimonials, daytime telephone contact, postal and email address and three competent referees not later than Thursday, 30th November 2023 by 5:00pm to:
Chief Human Resources Officer
Housing Finance Bank
Investment House
4 Wampewo Avenue, Kololo

Please take note that all applications should be sent by email to Recruitment@housingfinance.co.ug

DO NOT HAND DELIVER YOUR APPLICATION.
Please note that ONLY shortlisted candidates will be contacted and any form of canvassing will lead to automatic disqualification.

Guidelines for submitting Documents
1. Ensure that all your documents are scanned and submitted in 1 single batch using the following order:
• Application letter
• Curriculum Vitae (CV)
• Academic Documents and Certificates
2. The maximum document size is 10 MB
3. Please indicate the name of the position you are applying for in the subject.

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