Job Description

Architecture design, total solution design from requirements analysis, design and engineering for data ingestion, pipeline, data preparation & orchestration, applying the right ML algorithms on the data stream and predictions.

Hands-on programming and architecture capabilities in Python, Java, R, or SCALA

Experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Hidden Markov Models, Conditional Random Fields, Topic Modeling, Game Theory, Mechanism Design, etc.)

Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.)

Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, Qlik, etc.)

Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)

Hands on experience in RDBMS, NoSQL, big data stores like: Elastic, Cassandra, Hbase, Hive, HDFS and relevant open source systems

Demonstrated experience developing best practices and recommendations around tools/technologies for ML life-cycle capabilities such as Data collection, Data preparation, Feature Engineering, Model Management, MLOps, Model Deployment approaches and Model monitoring and tuning.

- Bachelor's degree or equivalent with minimum 6 - 10 (Engineer - Architect) years work experience