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Senior Data Scientist at Envision Employment Solutions
Dubai, Dubai, United Arab Emirates -
Full Time

Start Date

Immediate

Expiry Date

26 Feb, 26

Salary

0.0

Posted On

28 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Science, Machine Learning, Natural Language Processing, Model Architecture Design, Feature Stores, Model Monitoring, Ensemble Blending, A/B Testing, Model Explainability, Transformer-Based Models, Retrieval-Augmented Generation, Semantic Search, Vector Databases, Data Pipelines, APIs, CI/CD

Industry

Human Resources

Description
Envision Employment Solutions is currently looking for a Senior Data Scientist for one of our partners, a global leader in the IT Services and IT Consulting. Qualifications Bachelor’s or Master’s degree in Data Science, AI, or Computer Science. 4 to 6 years of experience is required, Strong record of production-grade ML/NLP projects. Experience leading small data science teams or research initiatives. Technical Requirements Deep expertise in model architecture design, feature stores, and model monitoring. Experience in ensemble blending, A/B testing, and model explainability (SHAP, LIME). Builds and fine-tunes transformer-based models for custom tasks (summarization, Q&A, document intelligence). Implements RAG (Retrieval-Augmented Generation) and embedding-based semantic search. Integrates vector databases (Pinecone, FAISS, Chroma). Uses LangChain or LlamaIndex for orchestration. Evaluates and optimizes prompt templates and context length efficiency. Designs data pipelines (Airflow, Spark, Dataiku). Deploys scalable APIs, manages CI/CD, monitoring, and drift detection. Works closely with product and engineering teams to embed AI in production systems. Leadership & Soft Skills Leads small teams or workstreams. Ensures project quality, deadlines, and alignment with business KPIs. Coaches mid-level team members and contributes to talent development.
Responsibilities
The Senior Data Scientist will lead small teams or workstreams, ensuring project quality and alignment with business KPIs. They will work closely with product and engineering teams to embed AI in production systems.