Data Science

As a Data Scientist, you will play a pivotal role in building and deploying machine learning models for various use cases such as sales propensity modelling, forecasting, and personalized recommendations. You will analyse structured and unstructured data, conduct text analytics, and provide actionable insights to improve customer and employee experiences. This role involves close collaboration with business stakeholders and team members to drive data-driven decisions, enhance operational efficiency, and deliver innovative solutions.

Key Responsibilities:

• Collaborate with stakeholders to understand business requirements and desired outcomes.
• Perform exploratory data analysis on structured and unstructured datasets.
• Develop, deploy, and monitor machine learning models, addressing performance issues and model drift.
• Conduct predictive and prescriptive analytics, generating actionable insights and presenting results.
• Integrate inference models with platforms like MS Dynamics.
• Research emerging trends in AI/ML and apply innovative techniques to solve business challenges.

Qualifications:

Basic:

• 2–6 years of experience with a Bachelor's or Advanced Degree (e.g., Master's, MBA, PhD).

Preferred:

• Master’s in Statistics, Data Science, Computer Science, or related fields.
• 3+ years of experience in data-driven decision-making or quantitative analysis.
• Expertise in Python, SQL/Hive, Spark, and data visualization tools (Tableau/Power BI).
• Strong background in machine learning, text mining, NLP, and deep learning techniques.
• Experience with frameworks like TensorFlow, PyTorch, and IBM Watson APIs is a plus.
• Familiarity with big data tools (Hadoop, Hive, Kafka) and data engineering concepts.
• Proficiency in database systems (SQL, NoSQL, Graph Databases) and Linux/Windows environments.
• Excellent communication and problem-solving skills.

Good to Have:

• Experience in building and scaling inference model APIs.
• Knowledge of microservices, ETL/ELT pipelines, and real-time streaming platforms.