Associate Lead - Data Scientist ( Python, AL/ML)
Overview
We are seeking a seasoned Data Scientist to lead the development and optimization of enterprise-wide search systems and AI-enabled features. This role involves designing algorithms, improving search accuracy, and deploying production-grade ML systems for ranking, personalization, and recommendations.
What You'll Do8
- 1Contribute to the development and optimization of enterprise-wide search systems and models.
- 2Design and implement algorithms to improve indexing, query relevance, and search accuracy.
- 3Support taxonomy, ontology, and metadata model creation for better search outcomes.
- 4Collaborate with business units to build AI-enabled search features.
- 5Conduct analysis of user behavior and system metrics to refine search performance.
- 6Develop production-grade ML systems for ranking, personalization, and recommendations.
- 7Participate in proof-of-concept initiatives with internal and external partners.
- 8Follow best practices in software engineering including CI/CD, testing, and monitoring.
Requirements7
- 15–8 years in Search, Information Retrieval, NLP, and Machine Learning.
- 2Strong knowledge of search technologies (indexing, faceted search, NLP-based search).
- 3Programming skills in Python, Java, or Scala.
- 4Familiarity with ML/DL frameworks: TensorFlow, PyTorch, scikit-learn, Keras.
- 5Experience with SQL/NoSQL databases (Cosmos DB, MongoDB, Cassandra).
- 6Exposure to CI/CD pipelines, Git, Jenkins, testing frameworks.
- 7Good understanding of data structures, algorithms, OOP concepts, and Linux.
Who Should Apply
This role is ideal for a senior data scientist with deep expertise in search, information retrieval, and machine learning, who thrives on building and optimizing enterprise-scale AI systems. The ideal candidate will have a strong background in NLP, hands-on experience with ML/DL frameworks, and a passion for improving search relevance and user experience.
Salary Insight
Open to discussion
Location
Required Skills
Application Tip
Highlight your experience with search technologies (e.g., Elasticsearch, Solr, Lucene) and provide specific examples of deploying ML-based search or recommendation systems at scale.
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How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
Only candidates who clear screening move forward.
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