Early Career Award in Statistics and Data Sciences (ECASDS)

The Early Career Award in Statistics and Data Sciences (ECASDS) recognizes and felicitates IISA members who have made outstanding contributions in all topics covered under the broad umbrella of statistics and data sciences. Awards will be given in three tracks: "Statistics and Data Sciences: Theory", "Statistics and Data Sciences: Applications" and "Statistics and Data Sciences: Interdisciplinary Studies and Practice".

For these Early Career Award in Statistics and Data Sciences (ECASDS), the eligibility requirements are as follows:

• For all three tracks: Nominees must be an active member of IISA for at least the past two years at the time of nomination, or a life member for any length of time.
• For the "Theory" and the "Applications" tracks: IISA members are eligible to be nominated for up to 13 years beyond the year of their terminal degree, or 41 years of age, whichever occurs later.
• For the "Interdisciplinary Studies and Practice" track: IISA members are eligible to be nominated for up to 17 years beyond the year of their terminal degree, or 45 years of age, whichever occurs later.
• In all tracks, the limits on age or time after terminal degree will be deemed as satisfied if these are satisfied on the first or January of the year in which the nomination is made. For example, a person can be nominated for the "Theory" track if their 42nd birthday is no earlier than January 1st of the year in which their nomination is filed.
• A terminal degree for the purpose of these awards are a PhD, MS, BS or their equivalents from a nationally or internationally recognized educational institution. IISA will not consider post-doctoral studies, optional practical trainings, curricular practical trainings, internships, apprenticeships, online training or online educational activities as degree programs for the purpose of these awards.
• A nominee will be required to show either a proof of age or a proof of graduation date once they are shortlisted for an award. A signed statement from a University Dean, Director, Head of Department or equivalent on official stationery is acceptable as a proof of graduation. A nationally or internationally recognized document like a passport, birth certificate, government-issued identity card or driver’s license is acceptable as proof of age.

Nomination procedure: In order to submit a nomination, please include

• a cover letter outlining the significance of the nominee's contributions,
• at least two but no more than three additional letters of support (each no longer than 2 pages preferably) that specifically comment on how the nominee meets the nomination criteria,
• a current curriculum vitae of the nominee, and
• no more than two published research papers or preprints authored by the nominee.

All the materials should be combined in a single PDF document and uploaded at the nomination portal. The size of the PDF cannot exceed the file limit specified in the portal.

Nominations can be made by any IISA member. Self-nomination is not acceptable. Letters of support can be written by individuals who are not members of IISA. All application materials should be submitted using the online system by the deadline. Multiple letters of support may be included with the nomination. The IISA awards committee will not make any of the submitted materials public, hence confidentiality should not be a concern.

Selection: The ECASDS selection committee is comprised of senior members of IISA who have been involved with IISA activities for a significant amount of time. Typically, one award is made in each track in a given cycle of nomination.The winners of these awards will typically be felicitated at a ceremony during the annual IISA conference. All queries regarding the ECASDS should be directed to awards@intindstat.org.

Guidelines for nominations in the "Theory" category: This award aims to recognize individuals who have made outstanding contributions in development of theoretical foundations in statistics and data sciences. Such contributions may include but are not limited to research in topics of mathematics related to statistics and data sciences, research in theoretical statistics and theory of machine learning, research in theoretical computer sciences. Individuals who have made outstanding research contributions in probability theory and mathematical studies of algorithms may be considered for this award. A successful candidate may demonstrate one or more of the following:

• Impactful original research in probability theory, mathematical studies of algorithms, theoretical and mathematical statistics and machine learning, optimization techniques and operations research.
• Development of data science and statistical methodology that simultaneously significantly advances theoretical knowledge in one or more disciplines.
• Multi-disciplinary research activities that contribute significantly to the knowledge in one or more disciplines, and contribute to the foundations of machine learning and statistics.

As appropriate, provide relevant documentation (e.g., publications, preprint, software vignettes and so on) that addresses the effectiveness of the candidate’s contributions and the results of those contributions.

Guidelines for nominations in the "Applications" category: This award aims to recognize individuals who have made outstanding contributions in development of methodology, algorithms, software products in statistics and data sciences, and outstanding collaborative research activities involving data sciences and other disciplines. A successful candidate may demonstrate one or more of the following:

• Development of innovative statistical and data science methodological and technical tools that have an impact in statistical practice and in collaborative research.
• Development of specialized software tools to advance research and practice.
• Multi-disciplinary research activities and case studies that contribute significantly to the knowledge in one or more disciplines.

As appropriate, provide relevant documentation (e.g., publications, preprint, software vignettes and so on) that addresses the effectiveness of the candidate's contributions and the results of those contributions.

Guidelines for nominations in the "Interdisciplinary Studies and Practice" category: This award aims to recognize individuals with an outstanding level of influence in the application of an existing statistical practice, or an innovation, that has strengthened the quality and efficiency. A successful nominee may demonstrate excellence in interdisciplinary research, in statistical consulting work or in professional applications of Statistics and Data Sciences at government and industry. A successful candidate is required to show significant statistical contribution in an applied field including but not limited to healthcare, finance, education, forestry, psychology, law, and marketing. A successful candidate may demonstrate one or more of the following:

• An unconventional application of an existing statistical methodology to a new area that has increased the quality and impact of the results.
• A new development in the statistical/data science methods for analyzing data that has led to further insights to the practical problem.
• An innovative or out of box techniques to communicate results (e.g., innovative graphics, efficient software development) showing the impact of statistician to a wide array of users.
• Leadership role in professional societies and working groups with impactful contributions.

As appropriate, provide relevant documentation (e.g., publications, software vignettes, patents, documents from within the candidate’s organization or beyond) that addresses the effectiveness of the candidate’s contributions and the results of those contributions.

Last Updated July 1, 2023.