Data Scientist

RED Global; Greater London; Hybrid; GBP 50,000 - 75,000; Full time

Job summary

RED Global (United Kingdom) is seeking a Data Scientist for a 12-month contract in London with a hybrid model (3 days per week in-office). You will work on a Mobile Intelligence Platform project and own end-to-end data features.

The role requires strong Python (3.11+), data integration, and production-grade dashboard development, plus expertise in AWS, SQL, REST APIs and time-series analytics. Collaboration with stakeholders is essential.

Qualifications

• Strong Python (3.11+), pandas and NumPy skills.
• Production-grade Streamlit dashboard development.
• Data integration using Snowflake, OpenSearch, REST APIs and SQL.
• AWS experience (boto3, S3, Parquet).
• Data visualization with Plotly, Matplotlib or Seaborn.
• Experience with Docker, Kubernetes, CI/CD and pytest.
• Knowledge of statistical analysis, anomaly detection and time-series analytics.
• Understanding of mobile app KPIs, iOS/Android analytics, app performance and stability.
• Experience with layered architectures and end-to-end feature ownership.
• Excellent communication and stakeholder management skills.

Skills

Python

pandas

NumPy

Streamlit

Data visualization

SQL

REST APIs

Plotly/Matplotlib/Seaborn

Time-series analytics

Mobile app KPIs

Stakeholder management

AWS

Tools

Docker

Kubernetes

CI/CD

pytest

Job description

Data Scientist - 12 Months - London (Hybrid, 3 days per week in the office)

RED now has a new contract opportunity for a Data Scientist to join one of our key partners on a Mobile Intelligence Platform project.

The contract is for 12 months, starting ASAP, with a hybrid working model (3 days per week in the London office).

Specific skills/experience required:

• Strong Python (3.11+), pandas and NumPy skills.
• Production-grade Streamlit dashboard development.
• Data integration using Snowflake, OpenSearch, REST APIs and SQL.
• AWS experience (boto3, S3, Parquet).
• Data visualisation with Plotly, Matplotlib or Seaborn.
• Experience with Docker, Kubernetes, CI/CD and pytest.
• Knowledge of statistical analysis, anomaly detection and time-series analytics.
• Understanding of mobile app KPIs, iOS/Android analytics, app performance and stability.
• Experience with layered architectures and end-to-end feature ownership.
• Excellent communication and stakeholder management skills.