12 plus years of experience in statistical modeling, data mining, analytics techniques, machine learning software development and reporting
8 plus years of applied experience in building / deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect their performance.
5 plus years of hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.
3 plus years of experience in building use cases / solutions especially around AI/ based on Cloud infrastructure and services such as Azure, GCP, AWS cloud platforms and On-premise environments.
Expertise with SQL, NoSQL, Python, R, Javascript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes etc.)
Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations.
Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.
Expertise with scaling pilot machine learning solutions to a large scale production environment using Databricks
Expertise with visualization tools such as PowerBI, D3JS etc.
Excellent written and verbal communication skills.