Posted on: 26/11/2025
Description :
Responsibilities :
Feature Engineering and Data Preprocessing :
- Work with raw data to perform data cleaning, transformation, and feature engineering to prepare datasets for analysis.
- Collaborate with cross-functional teams to gather and understand data requirements.
Model Deployment and Monitoring :
- Maintain, optimize, and scale recommendation engines used in FMCG or consumer goods environments to ensure high availability, accuracy, and low-latency performance across channels.
- Continuously improve recommendation models using advanced ML techniques such as collaborative filtering, content-based filtering, matrix factorization, and hybrid recommender systems.
Model :
Collaboration and Communication :
- Collaborate with product, marketing, and engineering teams to integrate recommendations into consumer-facing applications, personalization engines, or B2B retail platforms.
- Communicate complex findings and insights in a clear and understandable manner to both technical and non-technical stakeholders.
Continuous Learning and Research :
- Stay abreast of industry trends and advancements in data science and machine learning.
- Continuously enhance skills through training and self-directed learning.
Qualifications :
Education and Experience :
- Bachelor's or master's degree in computer science, Statistics, or a related field.
- years of proven experience as a Data Scientist.
Technical Skills :
- Strong proficiency in Python for data analysis, statistical modeling, and machine learning (e.g., pandas, scikit-learn, statsmodels, NumPy).
- Hands-on experience in developing recommendation engine & Graph embedding algorithms like GraphSAGE.
- Hands-on experience on handling Large Dataset using Azure Databricks and Azure Cloud is must.
- Strong understanding on Model Evaluation parameters.
- Experience with machine learning frameworks (e.g. PyTorch, scikit-learn).
- Strong knowledge of statistical analysis and data visualization tools.
Problem-Solving :
- Ability to translate business problems into analytical frameworks and develop data-driven solutions.
Communication Skills :
- Strong interpersonal and communication skills with the ability to explain complex concepts to non-technical stakeholders.
Team Collaboration :
- Demonstrated ability to work effectively in a collaborative team environment.
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