Remote Business Analyst - Norwegian

Turing

2d•Remote

About The Position

Turing is seeking candidates with strong analytical and English comprehension skills for a remote Business Analyst role. The ideal candidate will be responsible for reading, summarizing, and breaking down large content into smaller logical blocks, conducting online research to validate claims, and working with Large Language Models (LLMs) to solve analytical puzzles. This role is crucial for fine-tuning and improving LLMs, offering an opportunity to become an expert in leveraging AI and future-proof one's career in an AI-first world. Day-to-day activities involve answering analytical questions and creating scenarios to train LLM models, providing correct answers and explanations for complex problems that models might get wrong. No prior specialized domain experience is needed.

Requirements

Multilingual capabilities (English and Norwegian) are mandatory.
Good research and analytical skills.
Ability to provide constructive feedback and detailed annotations.
Creative and lateral thinking abilities.
Excellent communication and collaboration skills.
Self-motivated and able to work independently in a remote setting.
Ability to commit to 40 hours per week for the contract duration overlapping US hours.
Desktop/Laptop setup with a good internet connection.

Nice To Haves

Bachelors degree or undergraduate in Engineering, Literature, Journalism, Communications, Arts, Statistics, or a related field.
Experience writing professionally (business analysts, research analyst, copywriter, journalist, technical writer, editor, translator, etc).
Understanding of Excel and Google Suite.
Proficiency in Data interpretation, Logical reasoning and Basic arithmetic is highly desirable.

Responsibilities

Read, summarize, and break down large content into smaller logical blocks.
Conduct online research to validate claims made in content.
Work with LLMs to solve analytical puzzles.
Answer a variety of interesting analytical questions.
Create scenarios to train LLM models to improve their performance.
Provide correct answers and explanations for complex problems that models might get wrong.