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Data Scientist – Predictive Modeling & Business Analytics

TalkRemit · Égypte

New
Mid 🇬🇧 English
Python SQL Scikit-learn TensorFlow PyTorch Tableau Power BI Quicksight Matplotlib Seaborn AWS GCP Azure MLOps Model deployment Production monitoring OLAP LLMs Generative AI NLP Explainable AI Model fairness AI governance Real-time data pipelines Stream analytics

Job description

About the role

We are seeking a Data Scientist who transforms raw data into actionable insights that drive business growth. You will collaborate with cross‑functional teams to build predictive models, run experiments, and shape strategy through evidence‑based recommendations.

Key responsibilities

  • Design, develop, and deploy predictive models and machine‑learning algorithms to forecast trends and optimize outcomes.
  • Collect, clean, and analyze large structured and unstructured datasets to uncover meaningful patterns.
  • Plan and execute A/B tests and statistical analyses to validate hypotheses and inform product and business decisions.
  • Translate complex analytical findings into clear, actionable recommendations for technical and non‑technical stakeholders.
  • Partner with product, engineering, and business teams to identify data‑driven growth and efficiency opportunities.
  • Monitor, maintain, and refine deployed models as new data and business requirements emerge.
  • Advise leadership on data‑centric strategies that reduce costs, improve customer experience, and support organizational growth.

Required profile

  • Minimum 3 + years of experience in a data science or analytics role.
  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
  • Strong foundation in statistics, probability, and machine‑learning concepts.
  • Proven ability to communicate complex findings to non‑technical audiences.

Required skills

  • Python
  • SQL
  • R (optional)
  • Scikit‑learn
  • TensorFlow
  • PyTorch
  • Tableau
  • Power BI
  • Quicksight
  • Matplotlib
  • Seaborn
  • AWS
  • GCP
  • Azure
  • MLOps
  • Model deployment
  • Production monitoring
  • OLAP
  • Data warehouse
  • LLMs
  • Generative AI
  • NLP
  • Explainable AI
  • Model fairness
  • AI governance
  • Real‑time data pipelines
  • Stream analytics

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Published 1 day ago

Expires 1 month from now

6 views · 0 applications

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