Senior Data Scientist

Key duties and assignments

• Data preparation and business analysis
• To find chances for data-driven supply chain operations improvements, do a thorough business study.
• Assure data quality and integrity by preparing and cleaning data from many sources.
• Create and manage data structures and models to assist with analytics projects.
• Analyzing and Visualizing Data
• Apply sophisticated statistical and machine learning approaches to the analysis of intricate supply chain and logistics data.
• Create thorough data visualizations, dashboards, and interactive tools to efficiently convey findings.
• Convert unstructured data into insightful business information that informs supply chain management decisions.
• To optimize procedures and raise cost and efficiency, find trends, patterns, and anomalies in supply chain data.
• Modeling Data and Developing Pipelines
• Using technologies like Pandas or Apache Spark, create and implement scalable data models and ETL pipelines for supply chain data.
• Create and manage cloud-based data lake solutions to assist with machine learning and advanced analytics projects.
• Enhance data workflows to process massive supply chain datasets more quickly and effectively.
• Establish data quality checks and monitoring systems to preserve the integrity of supply chain data along the pipeline; work with data engineering teams to guarantee the smooth integration of data pipelines with current systems and data warehouses.

Project and Stakeholder Management

• Oversee and work together on several analytics projects, controlling deadlines, materials, and outputs.
• Work with stakeholders from various functional areas to comprehend business requirements and convert them into analytical solutions
• Control stakeholder expectations and make sure project outputs and business objectives are in line
• Deliver data-driven insights and recommendations to both technical and non-technical audiences
• Supply Chain AI Implementation
• Develop and execute AI solutions to support the company's self-sufficient supply chain projects
• Work with operations and IT teams to incorporate AI solutions into current workflows and systems
• Keep up with the latest developments in artificial intelligence and how they might be used in supply chain management
• Gen-AI prompt engineering
• Assess model performance and make iterations for enhancements

Qualifications:

• Five or more years of expertise in data science or advanced analytics, ideally in supply chain or related fields
• A bachelor's or master's degree in data science, statistics, mathematics, computer science, or a similar discipline Logistics
• Strong command of programming languages like Python; familiarity with data visualization software like Tableau, Power BI, and Plotly; and in-depth understanding of machine learning frameworks and algorithms like scikit-learn, TensorFlow, and PyTorch
• Knowledge with cloud platforms (like AWS and Azure) and big data technologies (like Spark)
• Strong communication skills with the capacity to explain intricate technical ideas to nontechnical audiences
• Familiarity with Agile methodologies and project management tools (such as Jira, GitLab, and Confluence)
• Demonstrated capacity to work both independently and cooperatively in a fast-paced setting
• Proven experience in project management and stakeholder engagement
• Strong dedication to data integrity and the ethical use of AI
• proactive "can-do" attitude and creative problem-solving abilities
• Adherence to all business policies, ISO, ICS, or comparable standards
• Readiness to continuously learn and adjust to new technologies and methodologies

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