Arrows
Senior Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist with 12-month rolling contracts, paying £700-£800 per day. Candidates must have experience with production-ready data science products, proficiency in Python, SQL, and cloud platforms (AWS or GCP), and be comfortable with ambiguity.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
920
-
🗓️ - Date
January 15, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Inside IR35
-
🔒 - Security
Unknown
-
📍 - Location detailed
United Kingdom
-
🧠 - Skills detailed
#Pandas #NumPy #BigQuery #Spark (Apache Spark) #PySpark #AWS (Amazon Web Services) #GCP (Google Cloud Platform) #Python #Snowflake #SQL (Structured Query Language) #Redshift #Data Science #SciPy
Role description
Urgent requirement x5 Snr Data Scientists
Start 1st week of Feb
🗓️ 12 month rolling contracts
📄 Inside IR35
💰 £700-£800 per day
🌍 UK, hybrid London (1 day office per week)
I need people who have worked on production ready applied data science products, we are not interested in research heavy backgrounds for this project.
You’ll be comfortable with ambiguity and will want to dive deep and fix problems at scale.
You will be able to develop the prototypes of the models, and do some feature engineering.
The environment looks a bit like this 👇
👉 Python (pandas, numpy, scipy, PySpark)
👉 SQL
👉 AWS or GCP (BigQuery / RedShift / Snowflake)
Urgent requirement x5 Snr Data Scientists
Start 1st week of Feb
🗓️ 12 month rolling contracts
📄 Inside IR35
💰 £700-£800 per day
🌍 UK, hybrid London (1 day office per week)
I need people who have worked on production ready applied data science products, we are not interested in research heavy backgrounds for this project.
You’ll be comfortable with ambiguity and will want to dive deep and fix problems at scale.
You will be able to develop the prototypes of the models, and do some feature engineering.
The environment looks a bit like this 👇
👉 Python (pandas, numpy, scipy, PySpark)
👉 SQL
👉 AWS or GCP (BigQuery / RedShift / Snowflake)
