Data Science Engineer - Machine/Deep Learning Models - R/Python/Scala

- Experience in research and development. Conference papers at reputed AI/ML platforms (ICML, NIPS, AAAI) will be a big plus,

- Experience in Time series modeling (classical methods like ARIMA, STL Forecast). Understanding and implementing active research in Time series forecasting (Bayesian Forecasting, Hierarchical Forecasting),

- Hands-on experience in implementing Deep learning models with textual data/ time series data (CNN, LSTM- s) will be a great plus,

- Expertise in SCALA (or) functional programming paradigm/ Python / R,

- Experience in big data technologies like Spark, Hive, Hadoop,

- Experience in understanding business needs and translating to a data-science problem,

- Knowledge of the Industry 4.0 process - inventory optimization, smart factory, times optimization, quality control, and industrial automation,Python

- Libraries : tensorflow, Keras, Numpy, sklearn, google-cloud-vision, pandas, imutils, ezdxf, imgaug, lxml, opencv-contrib-python-headless, scikit-image, matplotlib

Job Responsibilities :

- Review deployments, source codes, configurations, algorithms, models, repositories for completeness

- Identify missing libraries/codes, dependencies, code documentation

- Update technical documentation, code comments, etc

- Integrate the code into DevOps

- Testing - DevOps Pipeline & Deployment, Prepare simulation script for stress test, Test for horizontal & vertical scalability, Test for integration with Google OCR, AWS Textract, Active Directory, User Management, Test for performance, User Journeys"