Data Scientist at Proto Energy

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.