ML Scientist II - Search

About the Team:

What are we looking for

Education

• Bachelor's or Master's Degree in Data Science, Computer Science, Statistics, or a related field from a reputable institution.

Experience

• 3+ years of industry experience in Data Science and building Machine Learning models.
• Demonstrated experience in building and deploying machine learning models that handle large datasets.
• Experience in Search Data Science, Natural Language Processing (NLP) tasks, or Vector Search is a plus.

Technical Skills

• Strong foundational knowledge in Probability Theory, Statistics, and Machine Learning.
• Proficiency with machine learning languages and frameworks such as Python, Numpy, Pandas, Scikit-Learn, PySpark, TensorFlow/PyTorch, XGBoost/LightGBM.
• Understanding of A/B testing methodologies and experience in designing, implementing, and analyzing experiments to evaluate search algorithm performance.
• Familiarity with best practices throughout all stages of the Data Science lifecycle, including data preprocessing, model training, evaluation, deployment and monitoring.

Soft Skills

• Demonstrated ownership and ability to deliver results on data-driven projects.
• Capability to manage multiple priorities in a fast-paced environment.
• Technical aptitude to quickly gr/asp complex technical issues and communicate effectively with both technical and non-technical teams.

Responsibilities:

• Search Optimization

  : Analyze user behavior insights in search and develop high-quality machine learning algorithms to improve search relevance and ranking.

• Model Development

  : Lead and mentor other machine learning scientists to promote learning, growth, and success within the team.

• Continuous Learning:

  Stay updated on advancements in the field of Machine Learning and apply these learnings to improve search algorithms.

• Customer Focus

  : Understand customer needs and leverage technology to enhance the search experience on Nykaa's platform.

• Documentation and Reporting

  : Document models, experiments, and processes. Present findings and insights to stakeholders to inform decision-making.