ML Engineer — Deploying Models & Live Dashboards

Applied Data Science Partners Ltd.; Greater London; Híbrido; GBP 70 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Annual bonus

26 days leave

BUPA Healthcare

Development budget

Hybrid work Shoreditch

Remote 4 weeks/year

Latest tech equipment

Snacks & drinks

Autonomy & growth

Resumo da oferta

Applied Data Science Partners Ltd. is seeking a Machine Learning Engineer to design, develop and deploy data science solutions in real-world client projects.

You will work closely with our team to move from solution design to deployment, applying best practices and cutting-edge ML techniques. You will train models, transform data, and present insights via live dashboards, collaborating across data science and engineering disciplines.

Qualificações

• Experience with applied machine learning techniques in Python.
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Responsabilidades

• Participate in design, development, testing, and evaluation of data science solutions.
• Train and deploy state-of-the-art machine learning models.
• Build processes for extracting, cleaning and transforming data (SQL / Python).
• Ad-hoc data mining for insights using Python + Jupyter notebooks.
• Present insights and predictions in live dashboards using Tableau / PowerBI.
• Support presentation of findings to clients through documentation, calls and presentations.
• Adopt data science best-practice (Git / Docker / cloud deployment).

Conhecimentos

ML in Python

Git collaboration

Data analysis

Mathematics & statistics

Problem solving

Time management

Independent & team work

Ferramentas

Git

Jupyter

Tableau

PowerBI

Descrição da oferta de emprego

Applied Data Science Partners Ltd. is seeking a Machine Learning Engineer to design, develop and deploy data science solutions in real-world client projects.

You will work closely with our team to move from solution design to deployment, applying best practices and cutting-edge ML techniques. You will train models, transform data, and present insights via live dashboards, collaborating across data science and engineering disciplines.