Description

You will design, build, and deploy recommendation engines using collaborative filtering, clustering, and Generative AI.

Responsibilities

• Develop and implement machine learning models including decision trees, neural networks, and regression.
• Design data architectures for large-scale data processing and data-driven decision-making.
• Analyze complex datasets using Python and SQL to extract actionable insights.
• Communicate technical findings and statistical insights to cross-functional teams.
• Deploy machine learning models into production environments.

Required Skills

• 5-7 years of experience in data manipulation and statistical model building.
• Expertise in machine learning algorithms: Random Forest, Boosting, Trees, and Neural Networks.
• Proficiency in statistical methods: GLM/Regression, simulation, scenario analysis, and distribution properties.
• Experience with distributed computing tools: Spark, Hadoop, Hive, and Map/Reduce.
• Strong command of Python and SQL for data analysis and manipulation.
• Advanced knowledge of text mining and social network analysis.
• Experience deploying models within a production environment.
• Ability to use Databricks on cloud platforms (Azure, Google, or AWS).
• Master’s or Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.

Preferred Skills

• Experience working with healthcare data.
• Proficiency in data visualization using PowerBI, Tableau, Business Objects, D3, ggplot, Flask, or Django.

Key Skills

Education

Any Graduate