Key responsibilities of the senior data scientist will be

Data-Driven Market & Opportunity Analysis

• Collect, analyze, and interpret data to identify new market opportunities for payment technologies

• Conduct feasibility studies for product expansion using predictive modeling, customer behavior analysis, and competitive benchmarking

• Assess emerging fintech/DFS trends

Business Case Development         

• Quantify the cost and scalability of proposed technologies to prioritize initiatives

• Partner with business analysts to quantify project time/cost estimates using historical data

• Create executive-ready reports to justify digital initiatives to leadership

• Mine payment ecosystem data to propose ICT-enabled solutions

Detail Responsibilities

1.            Leadership and Strategy

• Lead the data science team in developing strategic initiatives.

• Define and implement the data science roadmap aligned with business objectives.

2.            Project Management

• Oversee data science projects from inception to completion.

• Ensure projects are delivered on time and meet quality standards.

3.            Data Analysis and Modeling

• Design and develop advanced analytical models to extract insights from large datasets.

• Apply machine learning and statistical techniques to improve business processes.

4.            Collaboration

• Work cross-functionally with other departments (e.g., IT, marketing, finance) to integrate data solutions.

• Collaborate with product teams to enhance data-driven decision-making.

5.            Mentorship and Team Development

• Mentor and train junior data scientists and analysts.

• Foster a culture of continuous learning and improvement within the team.

6.            Stakeholder Engagement

• Communicate complex analytical results to stakeholders in a clear and actionable manner.

• Gather requirements from stakeholders to ensure data solutions meet their needs.

7.            Research and Innovation

• Stay abreast of industry trends, emerging technologies, and best practices in data science.

• Experiment with new methodologies and tools to enhance data analysis capabilities.

8.            Quality Assurance

• Ensure data integrity and quality across all data science initiatives.

• Develop and enforce best practices for data handling and analysis.

9.            Performance Monitoring

• Establish key performance indicators (KPIs) to measure the success of data initiatives.

• Regularly review and report on the effectiveness of data strategies.

Skills Required

• Strong analytical and problem-solving abilities.

• Proficiency in programming languages (e.g., Python, R).

• Experience with data visualization tools (e.g., Tableau, Power BI).

• Familiarity with machine learning frameworks (e.g., TensorFlow, Scikit-learn).

• Preparing proposal

• Excellent communication and interpersonal skills.

• BSC/MSc in Data Science or Data Analytics or related fields of studies 
• 6/4 years of relevant work experience out of which 2 years in professional positions
• Ethical competence and certifications are advantages or competency in Python programming 

How To Apply

Qualified candidates are invited to submit their application with non-returnable CV, educational qualifications and work experience to hr@ethswitch.com, stating the title of the position clearly on the subject line. Qualified female applicants are highly encouraged.

*Please be aware that it is mandatory to attach your credentials (educational qualifications and work experience) along with your CV. Submitting only your CV is not sufficient.

*Please be advised that all applicants’ Educational Credentials will be verified with the respective higher institutions.