Data Scientist Seeking Feedback - Exceptional Promise

Hi all,

Hope everyone is doing well! Thank you to all the posters and reviewers in this forum for your work- it has been enormously helpful to read and learn from you all. I am looking for specific feedback on my application as a Data Scientist applying for Exceptional Promise. I graduated 3 years ago from university and have been working at Microsoft for the past three years in the same role.

Specific Questions:

  1. Not sure who to pick for my third recommendation letter, and worried that because my only >6 month job experience is at the same company, I can only pick recommenders from within this company. Is this a big concern that all my LoR and evidence are from the same job?
  2. Struggling to come up with “enough” evidence outside of rec letters and case studies on projects completed. I do not have experience speaking on panels or doing side projects outside of my work, nor substantive research experience. Is the listed evidence sufficient, or do I need to seek out opportunities that would strengthen this application first before submitting?

Recommendation Letters

  1. Mentor and Principal Data Scientist at company and leader of internal data science blog
  2. Senior Data Scientist at company with previous experience at other FAANG company
  3. [POTENTIAL] Mentor from internship (6 months), now tech lead at other FAANG company, published data science author
  4. [POTENTIAL] Principal data scientist who is currently skip and was previous boss
  5. [POTENTIAL] Senior Data Scientist at company with whom I’ve collaborated often

Mandatory Criteria

  1. Proof of high earning salary with comparison to comparable salaries in city/role translated to pounds
  2. Proof of success in job - promotion letter, stock bonuses, positive feedback documented in internal review forum
  3. Case study of a project I led that added a feature to our web app with millions of users and then turned into a paper that was accepted by our internal research publication

Optional Criteria 1: Innovation

  1. Case study of a pipeline I built to deploy ML models in production and run targeted A/B experimentation based on outcomes
  2. Case study of internal hackathon project using LLM to classify user intent
  3. Letter of recommendation from Senior Data Scientist colleague describing strong coding/ML expertise

Optional Criteria 3: Impact

  1. Case study of A/B experiment scorecard that I scripted and deployed and the hundreds of experiments that used it for measuring impact to determine whether or not to launch a feature
  2. Case study of data engineering/visualization project that led to new feature in web app for millions of users based on insights
  3. Documentation of code contributions to GitHub and where my code is referenced in other data scientists’ scripts

Hoping to submit my application within the next couple weeks and would greatly appreciate any and all feedback- thank you very much in advance!

@-ing @Francisca_Chiedu @Afolabi directly and everyone else who is kind enough to review, thank you so so so much for all you do!


Your MC is weak: only salary and employment proof predominantly is insufficient evidence to prove this criteria.

Ensure you add impact of work in case study and not just the work you did. Can you also attach a support letter highlighting your contribution and impact for this project?

Thank you @pahuja - this is super useful! I will consolidate the salary/employment proof into one piece of evidence, talk about the impact of the work in the case study, and add a letter of recommendation there to show impact as well. Do you think those three make a sufficient MC?

It’s not the strongest - without any public proof, MC is usually not strong in my opinion.