Develop an understanding of business obstacles, create solutions based on advanced analytics, and draw implications for model development.
Combine, explore, and draw insights from data. Often large and complex data assets from different parts of the business.?
Design and build explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques.
Prototype and pilot new solutions and be a part of the aim of ‘productifying’ those valuable solutions that can have an impact at a global scale.
Guides and coaches other chapter colleagues to help solve data/technical problems at an operational level, and in methodologies to help improve development processes.
Identifies and interprets trends and patterns in complex data sets to enable the business to make data-driven decisions.
Required Qualifications/Skills
Bachelor's degree in Computer Science, Information Technology, or related field
Expertise in statistical and machine learning techniques such as Logistic Regression, Tree-based ML algorithms (Random Forest, XGB), Deep Learning, and Natural Language Processing.
Highly proficient in R, Python, SQL, Spark, Azure AI Services, and other big data tools.
Good Knowledge of generative AI (Azure OpenAI, Lang chain, Embedding Models).