Description

You will lead data science initiatives and oversee the application of advanced statistical models to large datasets.

Responsibilities

• Lead the development and implementation of machine learning, statistics, and optimization models.
• Design and deploy classification models using ensemble techniques.
• Apply unsupervised learning models including K-Means, DBSCAN, and LOF.
• Implement NLP and deep learning architectures such as CNN and RNN.
• Manage large-scale data processing using distributed computing tools.

Required Skills

• 8-12 years of experience in a statistical or data science role.
• Expertise in Linear and non-Linear Regression, including Multiple and Multivariate models.
• Proficiency in Python, R, or Matlab for machine learning applications.
• Experience with distributed computing tools such as Map/Reduce, Hadoop, Hive, or Spark.
• Deep knowledge of machine learning, statistics, and optimization.
• Degree in Computer Science, Data Science, Mathematics, or a similar field.
• Experience working with large datasets and simulation/optimization.

Preferred Skills

• Experience with semi-structured or unstructured databases like MongoDB, Cassandra, ArangoDB, Couchbase, or GraphDB.
• Programming proficiency in C, C++, Java, or .Net.

Key Skills

Education

Any Graduate