Senior Data Scientist - Service Modernization (73505)
- Having an acute understanding of each customer's service profile
- Delivering superior service experiences proactively, preemptively and on-demand with an appreciation of the context, persona, and journey
- Using machine learning algorithms to optimize and automate an enterprise's service operation
Employing current and emerging technologies such as connected things, AR/VR, NLP for effective customer engagement.
Senior Data Scientist Role
Conceive and develop data science business requirements. Convert Data Science business requirements into ML models that the ML Engineer can deploy.
- Works with the business team and functional architect to outline detailed data science requirements
- Researches and develops statistical learning models for solving business problems
- Develops the data requirements in conjunction with the data architect for model training and validation
- Has responsibility for the overall functionality and associated outcomes of the models
- Works in close collaboration with the architects to create ML solutions
- Keeps up to date with latest technology trends
- Communicates results and ideas to key decision makers
- Implements new statistical or other mathematical methodologies as needed for specific models or analysis
- Works on data exploration, data analysis and presentation of data insights to the broader teams
- 15+ years of development experience with 7+ years practical experience with SAS, R, ETL, AI/ML, data processing, database programming and data analytics
- Deep expertise in developing causal analysis
- Strong leadership capabilities with experience in collaborating and leading, mentoring, and engaging teams
- A Bachelor's degree in Computer Science, Statistics, Applied Math, or related field is required. A Master's degree and Ph.D. in the same is a strong plus
- A solid track record of developing learning algorithms and systems, an extensive background in data mining and statistical analysis, and expertise in various data structures and common methods in data transformation
- Excellent pattern recognition and predictive modeling skills with a demonstrated ability to visualize data and present core insights in a clear and compelling way
- Extensive background in data mining and statistical analysis
- Candidate should be able to multi-task with rapid prototyping, agile development environments
- Ability to visualize data and present core insights in a clear and compelling way
- Able to understand various data structures and common methods in data transformation
- Experience with Machine/Deep learning software packages like TensorFlow, Spark ML, R, etc.
- Hands on experience in deep learning within areas of reinforced learning, computer vision, natural language processing, classification, regression etc.
- Proficient in machine learning tools like Jupyter notebook, python, and ML components in cloud (like Azure, GCP, OCI)
- Experience with Big Data technologies
- Strong industry and/or domain knowledge in Retail; Banking and Healthcare is a plus
- Experience with programming languages such as Java/SQL a plus
- Experience with Big Data technologies is a plus