Data Scientist – Lilongwe
At a glance
Mid-level Data Science role at QED.ai. Malawi · full-time.
Pay not stated Data Scientist salary
dataroles summary, based on the employer's posting.
What you'll do
- Build machine-learning systems, preferably for computer vision, using Python and relevant AI tools
- Use your understanding of AI to make decisions beyond treating models as black boxes
- Take part in daily code reviews, sharing your reasoning and responding to constructive feedback
What you bring
- At least three years working in machine learning, ideally including computer vision
- A strong record in competitive data modeling or notable research accomplishments
- Fluency in Python and core AI tools, plus clear spoken and written English
- Strong reasoning skills and the ability to give and receive feedback in code reviews
Who this fits
This role suits a mid-level data scientist with practical machine-learning experience and a thoughtful, collaborative approach to review. Full-time work of at least forty hours weekly is preferred; students with exceptional skills can contribute at least twenty-four hours a week.
From the employer
Basic Requirements
+3 years of experience in machine learning, preferably in computer vision
Respectable track record in competitive data modeling, and/or notable research achievements.
Well-versed with the latest trends with top-performing tools and the ML research community.
Strong fluency in both Python and in the main AI-related tools of the trade
Strong skills in logical reasoning and critical thinking, and the confidence to both express it and also receive constructive feedback through daily code review
Non-superficial intuitions about AI, beyond import blackbox
Highly preferred full-time employment of at least 40 hours per week. Promising students with exceptional skills should contribute at least 24 hrs/week.
Good fluency in English speaking and writing (typing > 35 wpm).
Critical thinking skills, expressiveness, and team-oriented attitude.
And you have to care about the work that you do!
Nice to haves
Working knowledge of statistics and basic probability.
Experience working with enterprise data warehouse software and/or data processing pipelines.
Experience working with datasets that cannot fit on a desktop, and systems engineering techniques for overcoming these constraints.
Evidence of leadership and team-building skills.
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