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Salary
$25k – $51k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 2+ years exp
Overview
Company
Impact
Profile match
Oneture is a cloud-first IT consulting, software engineering, and data analytics provider specializing in Amazon Web Services (AWS) architecture, cloud migration, big data engineering, and artificial intelligence integration. Headquartered in Mumbai, India, and founded in 2016, the enterprise provides end-to-end digital transformation services - encompassing custom SaaS application development, machine learning pipeline implementation, full-stack product engineering, and business intelligence.

We are looking for an enthusiastic Data Scientist to join our team based in Bangalore. You will be pivotal in developing, deploying, and optimizing recommendation models that significantly enhance user experience and engagement. Your work will directly influence how customers interact with products, driving personalization and conversion.

Responsibilities:

  • Model Development: Design, build, and fine-tune machine learning models focused on personalized recommendations to boost user engagement and retention.
  • Data Analysis: Perform comprehensive analysis of user behavior, interactions, and purchasing patterns to generate actionable insights.
  • Algorithm Optimization: Continuously improve recommendation algorithms by experimenting with new techniques and leveraging state-of-the-art methodologies.
  • Deployment and Monitoring: Deploy machine learning models into production environments and develop tools for continuous performance monitoring and optimization.

Requirements:

  • Experience: 2 - 4 years.
  • Technologies / Skills: Python, machine learning, NumPy, Pandas, Scikit-Learn, PySpark, TensorFlow, or PyTorch
  • Education level: Bachelor's degree (B. E. / B. Tech) in computer science or equivalent from a reputed institute.

Technical Expertise:

  • Strong foundation in statistics, probability, and core machine learning concepts.
  • Hands-on experience developing recommendation algorithms, including collaborative filtering, content-based filtering, matrix factorization, or deep learning approaches.
  • Proficiency in Python and associated libraries (NumPy, Pandas, Scikit-Learn, PySpark).
  • Experience with TensorFlow or PyTorch frameworks and familiarity with recommendation system libraries (e. g., torch-rec).
  • Solid understanding of Big Data technologies and tools (Hadoop, Spark, SQL).
  • Familiarity with the full data science lifecycle from data collection and preprocessing to model deployment.
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