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Data Scientist

As a Data Scientist at Markcov, you will be the analytical engine driving our retail strategy. Your purpose is to transform vast amounts of omnichannel retail data—from point-of-sale transactions to digital browsing behaviors—into actionable insights. You will build the predictive models that optimi

  • Location: Karachi
  • Type: Full-time · On-site
  • Experience: 3
  • Salary: 180000
  • Apply by: 30 Oct 2026
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About the role

As a Data Scientist at Markcov, you will be the analytical engine driving our retail strategy. Your purpose is to transform vast amounts of omnichannel retail data—from point-of-sale transactions to digital browsing behaviors—into actionable insights. You will build the predictive models that optimize pricing, forecast inventory demand, and personalize the modern shopping experience. The impact of your work will be felt directly on the bottom line as you empower our retail partners to anticipate market trends, reduce stockouts, and build lasting customer loyalty in a highly competitive market.

What you'll do

  • Design and deploy machine learning models to forecast product demand, optimize dynamic pricing strategies, and manage inventory lifecycles across physical and digital storefronts.
  • Develop advanced customer segmentation and churn prediction algorithms to power highly personalized marketing campaigns and improve Customer Lifetime Value (CLV).
  • Design, execute, and rigorously analyze A/B tests for promotional strategies, pricing models, and e-commerce user experiences to maximize conversion rates.
  • Translate complex, multi-dimensional data sets into intuitive dashboards and compelling commercial narratives for non-technical retail stakeholders and executive leadership.

What you'll bring

  • 3+ years of professional experience in data science, predictive modeling, or advanced analytics, specifically within the retail, e-commerce, or CPG industries.
  • Expert proficiency in Python or R for statistical analysis, along with advanced SQL skills for extracting and manipulating data from massive relational databases.
  • Deep hands-on experience with machine learning techniques relevant to retail (e.g., time-series forecasting, clustering, classification, recommendation engines) using frameworks like Scikit-learn, TensorFlow, or PyTorch.
  • Strong commercial acumen with a firm grasp of core retail metrics (e.g., basket size, sell-through rate, customer acquisition cost) and experience using BI tools like Tableau, Looker, or Power BI.

Why Markcov

  • Work on real growth challenges for real businesses
  • Learn alongside data scientists, engineers and marketers
  • Flexible, outcome-focused team culture