Reader in Statistics or Stat Data Scienc

Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package; plus the opportunity to buy more, great pension schemes and a number of health and wellbeing initiatives to support you.

The role

Applications are invited at Reader or Professor level in Mathematical or Statistical Data Science, broadly interpreted to include AI. The role will be based within the Statistics and Data Science section in the School of Mathematics, Statistics & Physics (MSP), with a flexible start date to be agreed. You will be expected to carry out excellent research and teaching in an area of Mathematical and/or Statistical Data Science which complements and strengthens existing activities within the School. In addition, there is an opportunity to engage with applied Data Science across a wide range of disciplines within the University, including the School of Computing and the Faculty of Medical Sciences. You will contribute to the research profile of the Statistics and Data Science Section within MSP by publishing in internationally recognised journals, demonstrating research impact, and securing external research funding. Additionally, you will be a key contributor to the Data Science 2030 (DS2030) faculty project to broaden our institutional offering in data science and, alongside the related AI2030 project, artificial intelligence. This will comprise a joined up educational offering at UG and PGT levels, and will be sector‑leading in providing forward‑facing data skills embedded in academic units across all parts of the university. DS2030 will act as a solid platform to build tangible cross‑institutional research and business engagement opportunities. DS2030 will be supported by strategic investment and the role holder will be a critical contributor to the success of the project.

Our aim is to employ a rich mix of colleagues with different backgrounds that will help us to:

• Contribute new ideas and different perspectives to both teaching and research.
• Provide diverse role models and attract a wide range of bright, active, and engaged students.

The University has developed an Academic Job Summary Guidance document that summarises the range of activities that academic staff may be expected to perform.

Key Accountabilities

The successful candidates will be expected to:

• Provide academic leadership in Mathematical and/or Statistical Data Science, shaping research direction and contributing to the strategic development of the school.
• Lead and contribute to interdisciplinary research initiatives across statistics and data science and related fields.
• Publish refereed articles in venues of international standing appropriate to Data Science.
• Collaborate with colleagues in the Statistics and Data Science section, and with colleagues from other disciplines within the university on applied Data Science.
• Seek out funding opportunities and develop grant‑funded research projects.
• Attract, supervise, and mentor doctoral researchers and postdoctoral associates across a broad range of Data Science disciplines.
• Build and maintain strategic links with industry, government and external stakeholders in order to contribute to the development of applied, methodological or theoretical Data Science.
• Lead the design and delivery of research‑inspired teaching.
• Deliver high‑quality teaching and assessment at undergraduate and postgraduate levels, and contribute to programme development, accreditation, and academic leadership in education.
• Carry out administrative duties as assigned by the Head of School and the School Executive Board.

The Person

Knowledge, Skills and Experience

• Excellent grasp of both the Mathematical and/or Statistical foundations of Data Science.
• An outstanding research profile commensurate with career stage, with a strong publication record in Mathematical and/or Statistical Data Science, evidenced by publications in leading venues and other esteem indicators appropriate to Data Science.
• A record of successful research income generation, either in own name or as a major contributor, with evidence of leading collaborative research success in statistics and data science.
• A strong track record of successful supervision of PhD students and postdoctoral researchers.
• Demonstrable ability to effectively teach at university level, including experience of programme development.
• Evidence of development of, and ability to deliver, innovative and effective teaching and learning materials across a broad range of statistics and data science modules with an ability to create ideas for course development at undergraduate and postgraduate levels.
• Experience of university leadership or significant administrative roles.
• Excellent written and oral communication skills, and ability to engage effectively across the academic unit, faculty and external stakeholders.
• Ability to proactively lead on ambitious academic initiatives such as Data Science 2030, that can contribute to our institutional portfolio in data science, for example, large‑scale funding opportunities and/or new education provision.
• Experience of leadership and management in academic or industrial settings, with the ability to motivate, empower, and support colleagues in a collaborative and consultative environment.
• Strategic thinking, with experience of contributing to organisational development and change.
• Significant experience of managing projects and leading a group of researchers (Desirable)
• Evidence of supporting cross‑disciplinary research (Desirable)

Additional Criteria –Professor

• An internationally recognised research leader with a substantial record of publications in leading journals, significant research funding, and demonstrable impact.
• A proven ability to lead large‑scale, collaborative research programmes or institutional initiatives.
• A sustained record of academic leadership, including contributions to School, Faculty, or national‑level strategy.

Attributes and Behaviour

• Ability to lead or co‑lead within Statistics and Data Science, setting clear direction, inspiring colleagues, and fostering a culture of continuous improvement and excellence.
• Strong interpersonal and team‑working skills, with a clear commitment to creating an inclusive, supportive, and high‑performing academic environment.
• Commitment to mentoring and developing early‑career researchers, while contributing positively to the wider life, culture, and success of the School.
• Demonstrates an ambitious, credible research vision aligned to School priorities, demonstrating thought leadership and long‑term impact.
• Demonstrates integrity, accountability, and resilience in the face of change, alongside a positive and responsive approach to student engagement and administrative support.
• An ability to advance equity and fairness in higher education through inclusive teaching, research, or professional practice, without compromising the legal protections for academic freedom and freedom of speech within the law.

Qualifications

• PhD or equivalent experience in Data Science, or closely related disciplines such as Mathematics, Statistics, or Machine Learning.
• A Higher Education teaching qualification or equivalent experience.

Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution. We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunity employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population. At Newcastle University we hold a Gold Athena Swan award in recognition of our good employment practices for the advancement of gender equality. We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a Disability Confident employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme. In addition, we are a member of the Euraxess initiative supporting researchers in Europe.