Senior Data Scientist - ML & Data Products (Remote)

AtkinsRéalis; United States; Hybrid; USD 120,000 - 160,000; Full time

Benefits offered by this job

Hybrid working culture

Flexible holiday allowances

Training and professional development

Competitive rewards package

Health and wellbeing benefits

Job summary

AtkinsRéalis in the United States is seeking an experienced data scientist to design and deploy AI and machine-learning solutions that address complex operational challenges. You will work across data lifecycle stages from ingestion to presentation, collaborating with product owners, data engineers and cyber specialists in a fast-paced Agile environment.

The role emphasizes production-quality Python and SQL, MLflow, PySpark and modern data platforms, with some client-site work and flexible

Qualifications

• Proven experience building production-quality ML/AI solutions.
• Strong Python and SQL skills with data preparation and model validation.
• Experience with distributed data processing and MLops tools.
• Ability to translate business needs into data-driven insights.

Responsibilities

• Design, develop and deploy statistical, insightful, AI and machine learning solutions to solve operational challenges.
• Explore large datasets to identify trends, patterns and actionable insights.
• Communicate findings and recommendations clearly to both technical and non-technical stakeholders.
• Contribute to development of innovative AI, machine learning and advanced analytics capabilities.
• Collaborate with Product Owners, Business Analysts and Data Engineers in an Agile environment.

Skills

Python

SQL

Machine learning

Spark

Git

Agile

Data science

Education

Degree in quantitative field

Postgraduate qualification in data science or AI (advantageous)

Tools

MLflow

JupyterHub

PySpark

VS Code

Git

Trino

Apache Iceberg

Job description

AtkinsRéalis in the United States is seeking an experienced data scientist to design and deploy AI and machine-learning solutions that address complex operational challenges. You will work across data lifecycle stages from ingestion to presentation, collaborating with product owners, data engineers and cyber specialists in a fast-paced Agile environment.

The role emphasizes production-quality Python and SQL, MLflow, PySpark and modern data platforms, with some client-site work and flexible