Python Developer

Information Tech Consultants; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

Information Tech Consultants seeks a hands-on Data Scientist to join their London team. You will build and productionize ML models, perform EDA and feature engineering, and work closely with product and engineering stakeholders to translate data into actionable insights.

The role emphasizes end-to-end ML workflows, collaboration across teams, and deployment and monitoring of models in production environments.

Qualifications

• Bachelor's or Master's degree in CS/DS/Stats/Math or related quantitative field.
• 2–5 years of professional data science experience or similar.
• Strong proficiency in Python and core DS libraries.

Responsibilities

• Model development, training, validation, and deployment of ML models.
• Perform EDA, data cleaning, feature engineering on large datasets.
• Write production-grade Python for data processing and modeling.
• Conduct A/B testing, hypothesis testing, and model optimization.
• Collaborate with product, engineering, and business stakeholders to share results.
• Support ML model deployment, monitoring, and maintenance.

Skills

Python programming

Analytical thinking

Problem solving

Storytelling

Education

Bachelor's or Master's in CS/DS/Statistics/Math

Tools

Pandas

NumPy

SciPy

scikit-learn

TensorFlow

PyTorch

SQL

NoSQL

Spark

Hadoop

AWS

Azure

GCP

Matplotlib

Seaborn

Tableau

Power BI

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.