Python Developer

Information Tech Consultants

Greater London

On-site

GBP 60,000 - 90,000

Full time

21 hours ago
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Job summary

Information Tech Consultants is seeking a Python Developer/Data Scientist in London to transform data into actionable insights and build production-ready ML models. You will work hands-on across the end-to-end ML lifecycle, from data wrangling to deployment, collaborating with cross-functional teams.

The role requires 2-5 years of experience, strong Python expertise, and proficiency with ML frameworks, data libraries, and cloud platforms. UK-based candidates only.

Qualifications

  • Bachelor's or Master's degree in CS/DS/Statistics or related field.

Responsibilities

  • Develop and deploy ML models (classification, regression, clustering) into production.
  • Perform EDA, data cleaning, feature engineering on large, complex datasets.
  • Collaborate with product and engineering teams to translate model results into business insights.
  • Write efficient, production-grade Python code and contribute to ML tooling.

Skills

Python
Pandas
NumPy
SciPy
scikit-learn
TensorFlow
PyTorch
SQL
Big Data
AWS

Education

Bachelor's or Master's in Computer Science, Data Science, Statistics, Mathematics, or related field

Tools

Spark
Hadoop
AWS
Azure
GCP
Tableau
Power BI
Jupyter

Job description

Python Developer

Location : London

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.
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