Senior /Principal Data Scientist

Newbridge; Singapore; On-site; SGD 180,000 - 320,000; Full time

Job summary

Newbridge is seeking a Senior or Principal Data Scientist to lead high-impact ML initiatives across an AI-native platform for ecommerce brands.

You will own end-to-end delivery of production models powering personalization, forecasting, search, pricing, and marketing automation, while mentoring other data scientists and setting technical direction.

Qualifications

• 10+ years in data science or applied ML for Senior, 8+ years for Principal.
• Expert in Python, SQL, and ML frameworks like PyTorch or TensorFlow.
• Deep ecommerce data understanding: cold start, seasonality, sparse events, ranking.
• Production experience: models with real-time inference, monitoring, and uptime.
• Strong software engineering: clean, testable code, latency and cost optimization.
• Clear communication to product, executives, and customers.

Responsibilities

• Own model ownership from design to deployment and monitoring.
• Lead applied research on embeddings, retrieval, fine-tuning, and online learning.
• Define and uphold coding standards, run RFCs, and mentor teammates.

Skills

Python

SQL

ML frameworks

Causal inference

Real-time inference

System design

Mentoring

Communication

Tools

PyTorch

TensorFlow

LLMs

Vector search

Feature stores

Job description

As a Senior or Principal Data Scientist, you will be a technical leader driving high-impact ML initiatives across AI-native platform. You’ll own end-to-end delivery of production models that power personalization, forecasting, search, pricing, and marketing automation for ecommerce brands. This is an IC role with high scope and influence. You’ll set technical direction, mentor other data scientists, and solve problems where no playbook exists.

Key Responsibilities

Model Ownership
Design, build, and deploy production ML models including recommender systems, LLMs for catalog enrichment and chat, demand forecasting, LTV and churn prediction, causal inference for incrementality, and anomaly detection. Own model performance from prototype to monitoring.

Applied Research
Tackle ambiguous commerce problems with rigorous science. Evaluate new techniques in embeddings, retrieval, fine-tuning, and real-time learning. Run offline experiments and design online A/B tests to prove lift.

Technical Leadership
Set the standard for code quality, experimentation rigor, and model review. Lead design discussions, RFCs, and postmortems. Mentor mid-level data scientists and raise the bar for the entire team.

ML Systems & Infrastructure
Work with Data and ML Platform to improve feature engineering, training pipelines, eval frameworks, and low-latency serving. Identify gaps in tooling and drive solutions that let the whole team ship faster.

Product Collaboration
Partner directly with PMs and engineers to scope AI features. Translate business goals into ML formulations, define success metrics, and ensure models ship with clear UX and measurable impact.

Data & Experimentation
Work with large-scale ecommerce datasets like clickstream, transactions, catalog, and ad data. Design experiments using CUPED, switchbacks, or geo-tests when standard A/B is not viable. Debug data quality issues that impact models.

Cross-functional Impact
Support strategic customers and GTM teams on complex POCs. Explain model behavior to non-technical stakeholders. Contribute to roadmap planning and influence what AI products we build next.

What You’ll Need to Succeed

• Experience: 10+ years in data science or applied ML for Senior, 8+ years for Principal. Proven track record shipping models to production at scale in ecommerce, marketplace, adtech, or B2B SaaS.
• Technical Depth: Expert in Python, SQL, and ML frameworks like PyTorch or TensorFlow. Strong foundation in ML fundamentals, deep learning, statistics, and causal inference. Experience with LLMs, RAG, or vector search in production.
• Domain Expertise: Deep understanding of ecommerce data and problems. You have worked on cold start, seasonality, sparse events, multi-objective ranking, or inventory-aware forecasting.
• Production Experience: You’ve taken models from research to 99.9% uptime services. Comfortable with real-time inference, batch pipelines, feature stores, and model monitoring.
• Research + Engineering Balance: Strong software engineering practices. You write clean, testable code and can optimize for latency and cost. You also read papers and know when to use state of the art vs. simple baselines.
• Communication: Explain complex modeling choices clearly to product, execs, and customers. Write crisp docs and present findings that drive decisions.

Bonus Points

• Experience with multi-armed bandits, contextual bandits, or reinforcement learning for personalization.
• Built or scaled large-scale retrieval or ranking systems for search or recommendations.
• Worked with messy product catalogs, NLP for SKU normalization, or computer vision for merchandising.
• Experience with privacy-preserving ML, clean rooms, or federated learning.
• Publications, conference talks, or open source contributions in ML or recsys.

Leveling Guidance

Senior Data Scientist: Owns a major model or product area. Can scope and deliver complex projects with minimal guidance. Mentors others.

Principal Data Scientist: Owns a portfolio of models or a technical pillar like forecasting or search. Drives org-wide technical strategy. Influences roadmap across multiple teams. Recognized as domain expert.

Why This Role Matters

Our client’s AI features are only as good as the models behind them. As a Senior or Principal Data Scientist, you will ship the intelligence that drives GMV, conversion, and retention for thousands of ecommerce brands. You’ll work on problems with massive datasets and direct business impact.