Data Scientist - ML & Predictive Analytics

NTT DATA UK - Bento Box; Greater London; On-site; GBP 60,000 - 90,000; Full time

Job summary

NTT DATA UK&I is seeking a Data Scientist to join our Data Practice, delivering enterprise-scale data platforms, analytics and AI-enabled decision support. You will contribute across model development, feature engineering, training and deployment, collaborating with engineers and consultants.

Ideal candidates will have 3–5 years in data science, strong Python and SQL, and hands-on ML library experience. Familiarity with Snowflake, Databricks and Fabric is advantageous.

Qualifications

• 3–5 years of commercial data science or analytics experience.
• Strong Python skills for data analysis and model development.
• Solid SQL skills and experience with large datasets.
• Knowledge of supervised/unsupervised learning, validation and evaluation.
• Experience with ML libraries such as Scikit-Learn and a DL framework (e.g., TensorFlow or PyTorch).

Responsibilities

• Develop ML models for forecasting, classification, recommender systems and anomaly detection.
• Perform exploratory data analysis, feature engineering and model evaluation.
• Build reusable notebooks and pipelines for repeatable ML delivery.
• Communicate insights and model outputs to business stakeholders clearly.
• Collaborate with data engineers, architects and consultants across Snowflake, Databricks and Fabric.

Skills

Python

SQL

Scikit-Learn

XGBoost

Deep Learning

Education

MSc or equivalent in Data Science/Statistics/Math/CS

Tools

Snowflake

Databricks

Microsoft Fabric

Azure

AWS

GCP

Job description

NTT DATA UK&I is seeking a Data Scientist to join our Data Practice, delivering enterprise-scale data platforms, analytics and AI-enabled decision support. You will contribute across model development, feature engineering, training and deployment, collaborating with engineers and consultants.

Ideal candidates will have 3–5 years in data science, strong Python and SQL, and hands-on ML library experience. Familiarity with Snowflake, Databricks and Fabric is advantageous.