Data Scientist

Role: To develop intelligent algorithms and predictive models for Customer Service specific use- cases. The candidate is expected to - apply mathematical, problem-solving, and coding skills to manage machine logs, notification data, extracting valuable insights. - combine advanced machine learning techniques with clinical domain knowledge to improve and optimize operational efficiency - explore new business opportunities enabled by data driven insights and propose them to the business stakeholders. - Strong ability to translate business needs into measurable analytics use cases and success criteria - Ability to validate data-driven models in real-world service environments and iterate based on operational feedback - Experience prioritizing analytics features based on product roadmap, technical feasibility, and expected business impact - Proven ability to collaborate closely with cross-functional stakeholders to align on use case scope, validation criteria, and deployment strategy - Experience working with domain experts (e.g. service engineers, clinical specialists) to incorporate domain knowledge into model development and interpretation What are my responsibilities? As a Data Scientist , you are required to: - Maintains network to customers, business experts and other subject matter experts to understand the business data analytics requirements, use cases and identify data analytics driven business opportunities. - Design & develop technical solutions to create meaningful insights for business. - Develop analytics models using AI techniques for business problems, using existing ML models, customizing the models. Develop validation strategies for the same. - Configure and deploy algorithms, select optimal tool and define visualization method/tool to display results - Process, manage, extract and cleanse data to apply Data Analytics in a meaningful way (supportive responsibility). - Determine sustainable processes to support fast growing data volumes and ensuring data quality and data accessibility together with the data architect (supportive responsibility). - Regularly scan the Data Science landscape to stay up to date with latest technologies, techniques, tools, and methods in this field Qualification : Master’s or Ph.D. in Computer Science, Data Science, Statistics, Biomedical Engineering, or related field. The candidate should have done course on the following topics for 1 semester (or equivalent): - Linear Algebra, (2) Statistics, (3) Artificial Intelligence, Machine Learning (4) Neural Networks (5) Data structures / Algorithms. Experience level : Minimum 5 years in software development with at least 2 - 3 years hands-on experience in Data Science. Desired Knowledge & Experience : - Good understanding of Statistics, Data analytics, Pattern recognition, Machine learning, Neural networks concepts. - Programming experience: - Language: Strong Proficiency in Python - Libraries : Pandas, NumPy, SciPy : packages, Keras with Tensorflow as backend - Experience in databases, data query languages (SQL), Kusto Query Language, Snowflake. - Experience in developing Predictive, Forecasting models, customizing the models, training, deployment, monitoring. - Experience in Azure cloud-based Data Storage and data analytics environment like (Azure BLOB, AZURE Databricks, Snowflake, Azure Data Factory), PySparc. - Working with data from different sources: - Machine Logs. File formats like Parquet files. - Unstructured data, experience in NLP - Experience in representing data in Graph Formats, usage of tools like Neo4J - Experience in creating dashboards, visualizations. - SW engineering skills (CI/CD test driven development, GitHub, etc.). - Knowledge of Agentic AI is additional advantage. Required Soft skills & Other Capabilities : - Analytical ability, Great attention to detail. - Drive and the resilience to try new ideas, if the first ones don't work - Collaborative approach to sharing ideas and finding solutions - Ability to work independently and in a global team environment. - Excellent communication skills, to explain your work to people who don't understand the mechanics behind data science. - Knowledge & experience in healthcare domain is preferred.