Discuss with C-level leadership, Engineers, Product Managers to formulate hypotheses, solutions and desired outcomes.
Act as Subject Matter Expert on ML, Data and AI statistical models and how they apply to business problems.
You will help to implement models in Machine Learning, Optimization, Neural Networks, Artificial Intelligence (Natural Language Processing), and other quantitative approaches.
Familiarity with Data Engineering techniques to gather, prepare, cleanse and transform data for analysis and AI automation, including data pipelines.
Familiarity with getting data from social media - twitter, instagram, reddit, facebook, etc.
Create prototypes, minimally viable products
Deliver meaningful insights and predictions
Demonstrate business value
Mentor and coach others in the team
Must Have:
A Bachelor/Master/PhD degree in Computer Science Engineering/Data Science/ Operations Research/Statistics/or a related technical degree.
Overall 8+ years of working experience
2+ years of hands-on working experience as Data Scientist with deep understanding of Machine Learning and AI algorithms- Linear Regression, Logic Regression, Decision Trees, K-Nearest Neighbors, Neural Networks, Random Forests, NLP/NLU, etc
1+ years of experience with different frameworks such as Tensor flow, PyTorch, Keros, SparkML.
2+ years of hands-on coding experience with languages such as Python, R, Scala, Go, etc.
Good experience with source control systems such as git
Good to Have:
Experience in microservices with container technologies like Docker/Kubernetes
Working experience with deploying and running services in Kubernetes
Experience with the AWS services (Examples: SageMaker, Comprehend, Lex, Rekognition, Transcribe, EKS, Lambda, S3, etc)
Experience with troubleshooting production systems.
Good understanding and use of CICD systems such as Jenkins, Gitlab, etc.