Principal – Data Scientist

Principal – Data Scientist

Requirements

• Masters degree or PHD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years experience in an analytics related field.
• Have deep understanding on neural networks, attention architecture and other DL and ML concepts.
• Familiar with statistical models, such as linear models, generalized linear models, experiment design, and testing.
• Have experience working with optimization problems.
• Proven records of solving business problems using deep learning and machine learning methods.
• Familiar with some of the DL packages such as Pytorch, Keras, Tensorflow.
• Strong software development skills in languages such as Python, SQL, R, Scala, Java.
• Have experience in involving in deployment and production process.
• Have experience working with cross-functional teams, such as engineering and product teams.

Responsibilities

• Lead high-caliber team to build large-scale time series forecasting systems.
• Integrate Global forecasting models (e.g., Temporal Fusion Transformers, Nbeats) to enhance forecasting precision and generate synthetic time series data for better model training.
• Develop data science systems and tools for retail; e-commerce applications.
• Leverage LLMS to summarize and build large scale chat applications.
• Train large scale neural networks and deploy them as automated batch pipelines using airflow.
• Deploy large scale forecasting pipelines modeling thousands of time series using batch pipelines.
• Establish cross-functional relationships to maintain win-win situation for the corporation.
• Collaborate with various product stakeholders and business owners to formulate and productionize a solution.

Preferred Qualifications

• Experience with Big Data processing and feature engineering using Spark
• Experience with training machine learning models through Cloud Services including Google Cloud Platform and Microsoft Azure
• Hands on experience of designing and training large DL models on GPU farm
• Causal inference expertise and experiences
• Knowledge on LLM is a plus