Associate Professor in Data Science / Statistics

About the University of Bristol:

The University of Bristol’s Mumbai campus is an innovative extension of its prestigious UK counterpart, established to promote academic excellence, global collaboration, and impactful industry engagement in one of the world’s most dynamic financial hubs. The campus offers a truly international and cross-cultural academic environment, combining the University’s rigorous academic traditions with the fast-evolving Indian and South Asian business landscape.

As part of a growing global network, the Mumbai campus serves as a hub for interdisciplinary learning, applied research, and thought leadership. Faculty members enjoy access to global partnerships, collaborative research opportunities, and the ability to contribute to high-impact academic programmes that prepare students to meet the challenges of an interconnected world.

Role Overview

We are seeking a highly motivated and accomplished Associate Professor in Data Science / Statistics to join our growing academic team at the University’s Mumbai Enterprise Campus (MEC), a flagship transnational education initiative of the University of Bristol set to open its doors in 2026, coinciding with the University’s 150th anniversary.

The role will lead on curriculum and research development, mentor junior faculty, and strengthen the University’s academic reputation through teaching, innovation, high-impact research and external engagement. The role will report to the Mumbai Enterprise Campus Associate Dean and have dotted lines reporting to and collaborating with the Head of School of Mathematics in the Faculty of Science and Engineering (S&E), and other relevant University senior leaders. This senior-level position is ideal for candidates with a strong academic profile, proven research excellence, and leadership capabilities within higher education.

Key Responsibilities

Leadership, Culture, and Engagement

• Provide distinguished academic leadership and operational capacity in both teaching and research within mathematical statistics or data science fostering an environment of scholarly excellence.
• Represent the university at national and international academic and professional forums, enhancing its visibility and reputation.
• Establish and nurture strategic partnerships with industry, academic institutions, and government agencies to support research initiatives and enrich the learning environment.
• Contribute substantively to departmental governance, administration, and operational delivery in close collaboration with senior leadership.
• Develop, coordinate, and deliver advanced undergraduate and postgraduate courses in areas ranging from mathematical statistics and machine learning to coding and algorithmics.
• Mentor junior and early-career faculty members, actively participating in their professional development and performance evaluation processes.
• Work collaboratively with Professional Services partners to deliver delegated administrative and governance duties.

Teaching

• Play a pivotal role in curriculum development and contextualisation, programme accreditation, programme enhancement and the maintenance of quality assurance standards within the university.
• Create a nurturing environment for excellence across the whole education offer.
• Promote innovative teaching strategies that improve student experience, transferable skills creation and employability prospects.

Research

• Maintain a sustained record of high-quality outputs in excellent, peer-reviewed academic publications or in other recognised discipline specific channels, actively contributing to the international discourse in mathematical statistics and data science.
• Initiate, lead, and secure funding for research projects with significant potential to contribute to scholarly knowledge and societal advancement.
• Provide support for other academic disciplines and interdisciplinary opportunities within the MEC.
• Ensure research strengths are matched and leveraged to develop teaching excellence and integrated in MEC programme offerings.
• Where applicable, supervise and mentor doctoral, postgraduate, and undergraduate research projects, ensuring the highest standards of academic rigor and integrity.

Essential Criteria

• A completed PhD in mathematical statistics and data science.
• Significant academic experience, including substantial post-PhD teaching and research achievements
• Proven academic leadership experience in teaching (e.g., programme coordination, research leadership, or departmental roles).
• Demonstrated excellence in teaching, curriculum design, and academic mentorship.
• Strong publication record in highly ranked peer-reviewed international publications, or in recognised equivalent discipline-specific channels, and ability to contribute to the school’s strategic research ambition to address global/societal challenges of our time.
• Evidence of excellent organisational and administrative skills.
• Excellent interpersonal, communication, and collaborative leadership skills.
• Demonstrates a proactive approach to professional development.
• Strong programming expertise.
• Expertise is machine learning and data science.

Desirable Criteria

• At least 10-12 years of academic experience post-PhD
• Track record of securing or leading externally funded research projects.
• Willingness and strong evidence to seek collaborations/engage with public, private and not-for-profit/charitable sectors.
• Experience supervising doctoral students
• A teaching qualification recognised by the UK Higher Education Academy or equivalent.

For any concerns regarding your application, kindly reach out to us at careers@daskalos.com