Data Science Engineer

Data Science Engineer

Requirements

• Strong proficiency in programming languages (Python, R, or similar) and data science tools (e.g., Pandas, NumPy, Scikit-learn)
• Expertise in statistical modeling, machine learning algorithms, and data mining techniques
• Proven ability to build and deploy predictive models in production environments
• Experience with data visualization tools (e.g., Tableau, Power BI)
• Strong problem-solving and analytical skills with a data-driven mindset
• Excellent communication and interpersonal skills
• Strong proficiency in cloud platforms (Databricks, AWS, Snowflake, or similar) and their data engineering capabilities
• Experience with CI/CD tools and practices for data pipelines
• Knowledge of data warehousing and data lake concepts
• Experience with ETL/ELT processes and tools
• Strong proficiency in machine learning algorithms and techniques, including time series forecasting and deep learning
• Experience in applying AI to solve complex business problems
• Knowledge of forecasting methodologies and tools
• Ability to evaluate the performance of forecasting models and refine them accordingly

Responsibilities

• Source and integrate data from various internal and external sources
• Cleanse, transform, and prepare data for analysis and modeling
• Develop data pipelines and automation for efficient data ingestion
• Design, build, and maintain scalable data pipelines using cloud platforms (Databricks, AWS, Snowflake, etc.)
• Implement CI/CD pipelines for data engineering processes, ensuring code quality and efficient deployment
• Optimize data ingestion, transformation, and loading processes for performance and cost efficiency
• Develop data quality checks and monitoring mechanisms
• Employ statistical and machine learning techniques (e.g., regression, classification, clustering, time series analysis, forecasting models) to build predictive models
• Conduct exploratory data analysis to uncover patterns, trends, and anomalies
• Develop and implement data-driven solutions to address complex business challenges
• Develop and implement AI-driven solutions to optimize supply chain processes and decision-making
• Utilize forecasting techniques to predict future trends and patterns in supply chain data
• Evaluate and select appropriate machine learning algorithms and techniques for different forecasting problems
• Create compelling visualizations to communicate complex insights to both technical and non-technical audiences
• Develop interactive dashboards and reports to enable data-driven decision making
• Deploy models into production environments and monitor their performance
• Refine models based on performance metrics and evolving business needs
• Manage and optimize cloud resources (compute, storage, networking) for data engineering workloads
• Implement security best practices for data and infrastructure
• Partner with business stakeholders to understand their needs and translate them into data-driven solutions
• Communicate complex technical concepts effectively to non-technical stakeholders

Preferred Qualifications

• Background and experience in SAP are a plus