Mary-Anne Hartley (Annie)

Data Scientist

https://talent.gravityer.com/mary-anne-hartley-annie

Annie-LiGHT

Key Strengths

Strong foundational experience in Python for data science and machine learning.
Demonstrated ability to work on complex, multimodal data processing pipelines (mmore, MultiModN).
Experience with LLM-related projects (mmore, LLMdissector) indicates relevance to modern AI trends.
Exposure to front-end technologies (TypeScript, JavaScript, Vue, HTML, CSS) for ML applications (disco, Topics_Visualization) suggests a broader skill set beyond pure data science.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects demonstrate a strong inclination towards research and development in AI/ML, particularly in multimodal processing and LLMs. The personal project 'disco' also highlights an interest in making ML accessible, which could align with collaborative and user-centric cultures. However, the single listed work experience as 'Data Scientist' at 'Annie-LiGHT' starting in 2026-06-29T22:19:58.003Z and marked as current, with an experience level of 0, suggests a potential discrepancy or future role, making it difficult to fully assess cultural fit based on professional experience. The breadth of personal projects indicates a proactive and self-driven individual.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test score is 0, providing no insights.

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Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

moove-model-selector

May 31, 2026 – Present

Prototype model selection and evaluation planning tool for context-specific healthcare AI benchmarking through MOOVE.

View Project

LLMdissector

January 3, 2026 – Present

LLMdissector — GitHub repository

View Project

mmore

November 27, 2024 – Present

Ever needed to take 8000 PDFs, 2000 videos, and 500 spreadsheets and feed them to an LLM as a knowledge base? Well, mmore is here to help you! mmore is a scalable multimodal pipeline for processing, indexing, and querying multimodal documents

View Project

MultiModN

May 17, 2023 – September 26, 2023

MultiModN – Multimodal, Multi-Task, Interpretable Modular Networks (NeurIPS 2023)

View Project

ml-project-2-amg66

December 22, 2021 – December 23, 2021

ml-project-2-amg66 created by GitHub Classroom

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Topics_Visualization

January 31, 2021 – December 23, 2021

Topics_Visualization — GitHub repository

View Project

disco

June 23, 2020 – Present

DISCO is a code-free and installation-free browser platform that allows any non-technical user to collaboratively train machine learning models without sharing any private data.

View Project

Key Strengths

Strong foundational experience in Python for data science and machine learning.
Demonstrated ability to work on complex, multimodal data processing pipelines (mmore, MultiModN).
Experience with LLM-related projects (mmore, LLMdissector) indicates relevance to modern AI trends.
Exposure to front-end technologies (TypeScript, JavaScript, Vue, HTML, CSS) for ML applications (disco, Topics_Visualization) suggests a broader skill set beyond pure data science.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test score is 0, providing no insights.

Mary-Anne Hartley (Annie)

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit