Experience with Python data analysis libraries (pandas, sklearn, numpy, scipy, and matplotlib), and Spark MLlib
Proficiency with Spark, Hadoop, Kafka, Hive, and SQL
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Solid software engineering skills, with proficiency in Python and experience in providing them as services
GIT, Python web framework Web2Py/Django/ Flask
Experience with data visualization tools, such as D3.js, GGplot, etc. is a plus
Selecting features, building and optimizing classifiers using machine learning techniques
Data mining using state-of-the-art methods
Extending company’s data with third party sources of information when needed
Enhancing data collection procedures to include information that is relevant for building analytic systems
Processing, cleansing, and verifying the integrity of data used for analysis
Doing ad-hoc analysis and presenting results in a clear manner
Creating automated anomaly detection systems and constant tracking of its performance
Model Deployments in Container Platform
Experience : 3-6 years
Qualification : BE / BTech / MS/MTech
3-6 years hands-on industry work experience designing and building large-scale data, machine learning, and analytics applications and pipelines that are well-designed, cleanly coded, well-documented, operationally stable, and timely delivered
3+ years proven experience in software engineering related to AI, ML or Data science
Ability to work with teams and individually in a highly dynamic and exciting environment.
Great communication skills
Good ability to anticipate issues and formulate remedial actions.
Sound interpersonal and team working skills.
Sound Knowledge of unit testing methodologies and frameworks