Lando Löper

Data Scientist

https://talent.gravityer.com/lando-loper

ML Solutions Engineer | AI for sustainability | AI regulation and responsible data use

NEEW

Key Strengths

Extensive personal project experience in Python, particularly in areas related to Data Science, Machine Learning, and Deep Learning (Bayesian Optimization, Time-Series Forecasting, Graph Neural Networks, Reinforcement Learning, Code Embeddings).
Demonstrated interest in advanced topics like JAX for numerical computation and deep learning.
Exposure to diverse programming paradigms with projects in Haskell (functional programming, decentralized identifiers) and Scala (event sourcing).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards research-oriented and complex technical challenges, which could indicate a good fit for an innovative and problem-solving culture. However, the lack of professional experience beyond a current role with a future start date, and the absence of team-based project descriptions, makes it difficult to fully assess cultural fit regarding collaboration and adaptability. The target role is Data Scientist, and the projects align well with this domain, but the breadth of technologies (Haskell, Scala) suggests a broad technical curiosity that might extend beyond typical Data Scientist responsibilities.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, indicating no completed assessment.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

boax

November 15, 2023 – February 11, 2025

Boax is a Bayesian Optimization library for JAX.

View Project

tsmixer-weather-forecast

October 10, 2023 – October 10, 2023

Kedro project of time-series-forecast of the multivariate weather using TSMixer.

View Project

reinforcement-learning-with-jax

May 11, 2023 – May 11, 2023

reinforcement-learning-with-jax — GitHub repository

View Project

ssi

October 17, 2022 – January 7, 2023

A Haskell implementation of Decentralized Identifiers and Verifiable Credentials

View Project

polysemy-es

January 21, 2022 – January 24, 2022

Experimental event-sourcing effects for polysemy.

View Project

GNN_Graph_Query-Matching

December 1, 2021 – April 25, 2022

Graph Neural Networks for Graph Query Matching Tasks

View Project

zio-es

October 13, 2021 – October 25, 2021

A type-safe library adding event sourcing concepts to the zio ecosystem.

View Project

darwin

September 13, 2021 – September 13, 2021

darwin — GitHub repository

View Project

ocd-detection

November 10, 2020 – March 18, 2023

The aim of this project is to make the assessment and treatment of OCD more accessible and effective.

View Project

code-embeddings

June 17, 2020 – August 19, 2020

The aim of this project is to improve the experience of developers with poorly documented code, when reaching out to the original authors is not an option.

View Project

Key Strengths

Extensive personal project experience in Python, particularly in areas related to Data Science, Machine Learning, and Deep Learning (Bayesian Optimization, Time-Series Forecasting, Graph Neural Networks, Reinforcement Learning, Code Embeddings).
Demonstrated interest in advanced topics like JAX for numerical computation and deep learning.
Exposure to diverse programming paradigms with projects in Haskell (functional programming, decentralized identifiers) and Scala (event sourcing).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. Psychometric test scores are 0, indicating no completed assessment.

Lando Löper

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit