Assistant Professor - Data Analytics and Financial Modeling, Financial Econometrics at James Hope University Business School

James Hope University Business School is a postgraduate university committed to learning, research and knowledge creation. We aspire to raise a community of people with exceptional qualities and leadership skills to help create value and proffer solutions to pressing global issues in our world today. Through our world class teaching, outstanding research institutions and scholarship programs, we are committed to improving the world today by educating aspiring leaders that would be a great service to the nation and world.

We are recruiting to fill the position below:

Job Title: Assistant Professor - Data Analytics and Financial Modeling, Financial Econometrics

Location: Lagos
Employment Type: Full-time

Responsibilities

• Deliver engaging and insightful courses at the graduate, and executive levels, integrating the latest advancements in Fintech and Analytics.
• Mentor and inspire students, guiding them to develop the skills and knowledge necessary to excel in the digital era of finance.
• Collaborate with faculty members and industry partners to drive interdisciplinary initiatives and promote thought leadership in Fintech and Analytics
• Conduct groundbreaking research in Fintech, Analytics, and related fields, contributing to academic discourse and informing industry practice.

Additional fields of interest include, but not limited to:
Financial Data Privacy and Security:

• Conduct research on data privacy regulations, cybersecurity threats, and information security practices in financial services.
• Develop and teach courses on financial data privacy, cybersecurity, and digital identity management.
• Mentor graduate students in conducting research on topics such as data encryption, secure authentication methods, and regulatory compliance.
• Publish scholarly articles in academic journals on topics related to financial data privacy, cybersecurity, and risk mitigation strategies.
• Collaborate with industry partners, government agencies, and cybersecurity firms to enhance data security practices and protect financial systems from cyber threats.

Data Analytics and Financial Modelling:

• Conduct research on data analytics methodologies, financial modelling techniques, and predictive analytics in finance.
• Develop and teach courses on data analytics, quantitative finance, and financial modelling.
• Supervise graduate students in conducting empirical research using financial datasets and statistical techniques.
• Publish scholarly articles in academic journals on topics such as quantitative finance, risk management, and predictive modelling.
• Collaborate with financial institutions, investment firms, and data providers to develop analytics-driven solutions for financial decision-making.

Risk Management, Banking Regulations and Compliance:

• Conduct research on risk management practices, regulatory compliance, and financial stability in the context of FinTech.
• Develop and teach courses on financial risk management, regulatory compliance, and governance in financial institutions.
• Advise graduate students on research projects related to risk assessment, compliance frameworks, and regulatory technology (RegTech).
• Publish scholarly articles in top-tier journals on topics such as risk modelling, stress testing, and regulatory compliance.
• Collaborate with regulatory agencies, financial industry associations, and risk management professionals to address challenges and develop best practices in FinTech risk management and compliance.

Algorithmic Trading and Market Microstructure:

• Conduct research on algorithmic trading strategies, market microstructure, and high-frequency trading in electronic markets.
• Develop and teach courses on algorithmic trading, market microstructure, and quantitative trading strategies.
• Supervise graduate students in conducting research on topics such as algorithmic execution, market liquidity, and market impact analysis.
• Publish scholarly articles in leading journals on topics related to algorithmic trading, market efficiency, and market microstructure.
• Collaborate with financial institutions, trading firms, and exchanges to analyse market data, develop trading algorithms, and improve market efficiency and transparency.

Blockchain and Cryptocurrency:

• Conduct cutting-edge research on blockchain technology, cryptocurrency economics, and their applications in financial services and beyond.
• Publish scholarly articles in top-tier academic journals, presenting original research findings and contributing to the advancement of knowledge in the field.
• Secure research grants and funding to support research projects and initiatives related to blockchain and cryptocurrency.
• Develop and teach courses on blockchain fundamentals, cryptocurrency economics, and FinTech innovations. Design curriculum modules and learning materials that cover theoretical concepts, practical applications, and real-world case studies in blockchain and cryptocurrency. Incorporate hands-on exercises, simulation projects, and industry guest lectures to provide students with practical experience and exposure to industry best practices.
• Mentor graduate students, guiding them in conducting research projects, thesis work, and dissertations related to blockchain and cryptocurrency. Provide academic advisement and career guidance to students interested in pursuing careers in FinTech, blockchain development, or cryptocurrency-related fields.
• Stay abreast of the latest developments, trends, and regulatory changes in blockchain and cryptocurrency, attending conferences, workshops, and professional development programs.
• Serve on academic committees, departmental boards, and university task forces, contributing to the governance, strategic planning, and academic leadership of the institution.
• Engage in outreach and public engagement activities, raising awareness of blockchain and cryptocurrency concepts, benefits, and risks among students, faculty, policymakers, and the broader community.
• Contribute to academic committees and public engagement efforts.

Qualifications

• A Ph.D. or equivalent terminal Degree in Finance, Economics, Computer Science, or a related field.
• Demonstrated expertise in Fintech, Analytics, Machine Learning, Blockchain, or other relevant areas.
• A strong record of scholarly publications and/or industry experience, showcasing thought leadership and impact in the field.
• Experience in teaching and curriculum development, with a commitment to student-centred learning and innovation.
• Proven ability to collaborate effectively with colleagues and engage with industry stakeholders.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should send their Cover Letter, Curriculum Vitae, Evidence of teaching effectiveness (e.g., course evaluations), and Contact information for three references merged into a single PDF / Word document as an attachment to: [email protected] using the Job Title as the subject of the mail.

Note: Review of applications will start immediately, and applications will continue to be accepted until the position is filled.