Manager, SAP Data Scientist

Key Skills

Big Data Technology, Data Analysis, Data Engineering, Data Mining, Data pipelines, Data science techniques, Data Visualization, Design, DevOps, Docker, Infrastructure as code, Kubernetes-K8s, Linear Algebra, Machine learning techniques, Mathematical modeling, PySpark, Python Programming, R Programming, SAP, Scala Programming, SQL

Job Description

This a data scientist role in the SAP innovation team in Pfizer Digital’s Supply Chain Solutions Organization. The iERP innovation team develops SAP operational analytics and machine learning solutions that enable digital transformation for our customers. The data scientist will analyze customer's business problems, use cases and develop mathematical models and algorithms to solve these problems, and help our customers understand and implement the results of the analysis.

Job responsibilities and tasks:

• Work directly with business and creation center subject matter experts to translate our customers’ business needs into mathematical models and present and deliver solutions to clients. Oversee the entire machine learning lifecycle (research, design, experimentation, development. deployment, monitoring, and maintenance)
• Maintain and optimize machine learning models, identify new ideas to evolve them, develop new ones & benchmark possible solutions
• Research & implement best practices to enhance existing machine learning infrastructure
• Implement machine learning algorithms and libraries
• Analyze large and complex data sets to derive valuable insights
• Collaborate with data engineers to develop data and model pipelines
• Responsible for work packages related to Data Mining topics, specify and design data mining methods and integrate or implement these into products
• Create prototypes and work closely with the engineering team to deliver features into the product, evaluate and define test strategies for delivering high quality product features and capabilities of the product
• Evaluate and test data mining methods and maintain a high level of quality.
• Create data definitions and contribute to data storage infrastructure for data mining purposes and to Data Mining architecture
• Resolve data mining performance issues and monitor data mining system performance and implement efficiency improvements
• Implement data mining algorithms if required, work closely with product management, application developers, information developers and end users
• Lead small project teams of researchers or participate in such projects as key contributor, perform functional and empirical analysis on data mining topics, conduct research on data mining tools and algorithms, implement prototypes and data mining algorithms and validate them on real data
• Explore data sources, implements data exploration, pre-processing and data cleansing on the historical data
• Understand data and evaluate data quality from both data science and business value perspectives
• Prepare the data for future models
• Develop statistical / machine learning models based on the pre-processed data as a proof-of-concept
• Assess and optimize the model quality based on technical level by tuning hyper-parameters, settings or even changing the models
• Integrate the statistical / machine learning models into product
• Work with application developers, machine learning engineers closely to ensure the model is ported into the product based on the prototyping
• Work with product managers and designers to ensure all the features are delivered.
• Evaluate and improve the model performance under business context
• Refine the model by tuning hyper-parameter, adjusting data sources or model approaches to resolve the business problem of customer

Work Experience needed:

• Minimum 4 years’ experience in the following: regression modeling, machine learning, natural language processing, data analysis, application of distributed systems to scale solutions, database design, linear algebra, calculus
• Experience must include 4 years in the following: Foundation topics in Linear Algebra, Probability & Statistics, Multivariate Calculus; programming with SQL, Python, R; working with big data preferably in a productive project
• Minimum of 4 years of experience in SAP Native HANA Modeling and development
• Experience must also include supervised and unsupervised Machine Learning algorithms and deep learning frameworks; Data Visualization; data wrangling, developing pipelines for Machine Learning and data preparation activities for developing a Machine Learning application; and Distributed Application development
• Extensive knowledge of machine learning evaluation metrics and best practices, building, validating and evaluating of machine learning model, designing and implementing machine learning pipelines in production environments & experience in architecting, training and analyzing deep learning models
• Experience with building big data pipelines and Data Manipulation /data analytics / datamanagement / Big data system
• Ability to perform technology selection and technology evaluation
• Experience in modern DevOps practice and ability to establish CI/CD process and Docker & Kubernetes
• Industry experience with writing code (e.g., Python, Scala, PySpark, JavaScript) and taking ML models/ algorithms to production
• Strong analytical skills, results-oriented, customer-oriented attitude, good strategic and conceptual thinking skills
• Ability to present complex information in a clear and concise manner

Education and Qualifications/Skills and Competencies:

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field of study and 8 years of experience required or Master's degree and 5 years of above experience required.