Must have skills
Strong problem solving skills
Project management skills
Good analytical skills
Excellent planning and organization skills
Attention to details
Strong team player with the ability to work independently
Good communication skills
Self-motivated and able to work under pressure in a fast paced environment
Flexible
Qualifications
A bachelor’s degree in computer science, statistics, data science or equivalent qualification.
A master’s degree in computer science, statistics or data science is an added advantage.
Proven prior experience of 3 years in the same role.
Proficiency in programming languages such as Python or R, data manipulation tools, statistical modeling techniques, and machine learning algorithms.
Knowledge of data visualization tools and techniques (e.g., Matplotlib, Tableau, R shiny)
Solid understanding of databases and SQL for data extraction and manipulation.
Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and distributed computing is advantageous.
Experience with big data technologies (e.g., Hadoop, Spark).
Certificate of good conduct.
Job Role
Data analysis: Apply statistical and analytical techniques to explore and analyze complex data sets, identifying patterns, trends, and correlations.
Model development: Develop predictive models, machine learning algorithms, and statistical models to solve specific business problems or make accurate predictions.
Data preprocessing: Clean, transform, and preprocess data to ensure data quality and compatibility with analysis and modeling techniques.
Data visualization: Create clear and visually appealing data visualizations and reports to communicate complex findings to non-technical stakeholders effectively.
Collaborative problem-solving: Work closely with cross-functional teams and internal domain experts to understand business challenges and develop data-driven solutions.
Experiment design and hypothesis testing: Design experiments and conduct hypothesis testing to validate assumptions and assess the impact of different factors on outcomes.
Data storytelling: Translate technical findings into actionable insights and compelling narratives that drive business decisions and strategy.
Algorithm selection and optimization: Identify the most suitable algorithms and techniques for specific data analysis tasks and optimize them for efficiency and accuracy.
Continuous learning and improvement: Stay up to date with the latest data science tools, techniques, and methodologies. Continuously improve skills through self-learning, training, and collaboration with peers.
Perform any other duty(ies) as will be assigned from time to time by the supervisor or management.
Apply via :
hris.peoplehum.com
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