Job Description
🧠 Data Scientist: Machine Learning \& Python Specialist 🐍
Python Developer
Location
London
Work mode
Onsite
Experience:
2–5 years
**UK based candidates only - CITIZEN \& DEPENDENTS**
We are seeking an innovative and results-driven
Data Scientist
with a strong focus on
Machine Learning
and deep proficiency in
Python
. You will be instrumental in transforming complex data into actionable insights, building predictive models, and driving business strategy using cutting-edge analytical techniques. This role is for a hands-on individual who is excited to move models from the lab into production.
Key Responsibilities
- Model Development \& Implementation:
Design, develop, train, validate, and deploy advanced
Machine Learning
models (e.g., classification, regression, clustering, deep learning) to solve complex business problems.
- Data Wrangling \& Analysis:
Perform comprehensive Exploratory Data Analysis (
EDA
), data cleaning, feature engineering, and transformation on large, complex, and sometimes unstructured datasets.
- Coding \& Automation:
Write production-quality, highly efficient, and scalable code primarily in
Python
for data processing, analysis, and model creation.
- Experimentation \& Optimization:
Conduct A/B testing, hypothesis testing, and rigorous model validation, continually iterating and tuning algorithms to maximize performance, accuracy, and efficiency.
- Collaboration \& Communication:
Work closely with cross-functional teams (e.g., product managers, engineers, business stakeholders) to define project scope, interpret model results, and clearly present data-driven recommendations to both technical and non-technical audiences.
- Deployment \& MLOps:
Collaborate with ML/Data Engineers to deploy, monitor, and maintain ML models in a production environment, ensuring stability and performance over time.
Required Skills and Qualifications
Technical Expertise (The Core)
- Programming:
Expert proficiency in
Python
and its core data science libraries
Pandas, NumPy, and SciPy
.
- Machine Learning:
Deep, practical experience with popular ML frameworks and libraries
scikit-learn, TensorFlow, or PyTorch
.
- Statistics \& Math:
Strong foundation in
statistical modeling
, probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics.
- Databases \& Querying:
Proficiency in
SQL
for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases is a plus.
- Big Data/Cloud:
Experience with big data tools (
Spark, Hadoop
) and cloud computing platforms (
AWS, Azure, or GCP
) for scalable ML workflows.
- Visualization:
Ability to create clear, compelling data visualizations using tools like
Matplotlib, Seaborn, Tableau, or Power BI
to communicate insights.
Education \& Experience
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
- [Number] years of professional experience as a Data Scientist or in a highly quantitative role.
Soft Skills (Your X-Factor)
- Curiosity:
A strong passion for data and an inherent curiosity to explore, question, and challenge assumptions.
- Problem-Solving:
Excellent analytical and structured thinking skills to tackle complex, ambiguous business problems.
- Storytelling:
The ability to translate complex statistical and ML outputs into simple, business-relevant narratives and recommendations.