DATA SCIENCE ENGINEER – APPLIED AI & DECISION INTELLIGENCE

Classification: Senior Individual Contributor
Engagement: Long-term client project with immediate start

About the Opportunity

We are hiring Data Science Engineers to help build and operationalise the intelligence layer of an AI-native cloud automation and FinOps platform. This is a client project under NDA, the client is a technology company developing a portfolio of intelligent cloud operations products with a strong focus on decision intelligence and autonomy governance.

This team focuses on transforming high-volume operational telemetry, cost data, and decision outcomes into reliable data pipelines, feature sets, and evaluation frameworks that support automated and governed cloud decision-making.

Unlike traditional research-oriented data science roles, these positions are focused on production systems and operational intelligence. You'll work closely with the AI Architect and platform engineering teams to ensure that models, signals, and decision metrics operate continuously and reliably.

The ideal candidate is comfortable working across data engineering, experimentation, and applied machine learning in a cloud-native environment.

What You'll Be Doing

• Designing and maintaining data pipelines that ingest telemetry, billing, and operational data from cloud environments
• Developing feature engineering workflows supporting optimisation, anomaly detection, and trust scoring
• Designing mechanisms to detect data quality issues, drift, and inconsistencies in telemetry and model inputs
• Creating evaluation frameworks that measure decision quality and operational impact
• Building predictive models related to cost efficiency, performance optimisation, and anomaly detection
• Ensuring reproducibility and versioning of datasets, transformations, and experiments
• Collaborating with backend engineers to integrate models and signals into production services
• Monitoring model and data performance to detect drift, anomalies, or degradation
• Documenting assumptions, model limitations, and evaluation methodology
• Supporting experimentation and learning loops that improve platform automation over time

What We're Looking For

You are a pragmatic data scientist or data engineer who values operational impact over theoretical perfection.

• 5+ years of experience in data science, applied machine learning, or data engineering
• Experience building or supporting production data pipelines or ML systems
• Experience working on systems that operate continuously in production environments
• Strong statistical reasoning and experimentation mindset
• Ability to collaborate effectively with engineers and platform architects
• Comfort working in evolving early-stage environments where specifications may change
• Experience working with operational telemetry, infrastructure data, or financial/cost datasets is a strong advantage

Technical Requirements

• Strong Python data stack (pandas, NumPy, scikit-learn or similar)
• Experience building and maintaining production data pipelines
• Understanding of feature engineering and model evaluation workflows
• Familiarity with data versioning, lineage tracking, and reproducible pipeline design
• Experience with SQL and analytical data platforms (ClickHouse, BigQuery, Snowflake, etc.)
• Experience working with event-driven or streaming data pipelines is a strong plus
• Understanding of model lifecycle management and monitoring
• Experience with experiment tracking and dataset versioning
• Exposure to cloud-native environments and containerised workflows
• Experience integrating ML signals into backend services is beneficial

Other Requirements

• Excellent spoken and written business English
• Ability to iterate quickly on evolving datasets and collaborate effectively across engineering and research teams
• Flexibility during collaboration phases and comfort working in an evolving, early-stage environment
• Infrequent travel within Europe may be required for team meetings or partner engagements
• Knowledge of additional languages is an asset

Why This Project?

This is a rare opportunity to join a greenfield data science and decision intelligence effort where your work directly shapes how an AI-native platform learns, decides, and improves. The client is building defensible, patent-worthy technology in cloud operations intelligence. You'll work alongside an experienced AI Architect and platform engineering team, with real ownership over production data and model systems from day one.

Hiring managed by Mosano / Itpicker. Client details shared under NDA during the interview process.