[Hiring] Senior Data and Machine Learning Scientist @hireVouch

Role Description

As a data scientist, you'll play a pivotal role in developing and enhancing our innovative supply chain solutions. You'll collaborate closely with a talented team of passionate engineers and industry experts, applying data engineering and data science techniques to optimize supply chain processes. Your expertise will directly contribute to providing our clients with real-time visibility, predictive analytics, and actionable insights.

• Develop and implement machine learning models to improve the accuracy of supply chain ETAs.
• Analyze large, complex datasets to extract meaningful insights and identify trends.
• Design, build, and maintain scalable data pipelines and data lakes to ensure efficient data flow and storage for analytics purposes.
• Collaborate with cross-functional teams to integrate analytics solutions into our products.
• Design and build data visualization tools to communicate findings to stakeholders.
• Continuously research and apply the latest techniques in AI and machine learning to supply chain problems.
• Contribute to the development of our analytics product suite, ensuring scalability and efficiency.
• Communicate complex data science concepts to non-technical stakeholders.

Qualifications

• BS or MS degree in Data Science, Statistics, Computer Science, or a related field.
• Proven experience in machine learning, statistical modeling (5+ years).
• Proficiency in programming languages such as Python or R.
• Experience with SQL and working with large datasets.
• Strong expertise in designing and building robust data pipelines, data lakes, and optimizing data storage and retrieval structures.
• Knowledge of supply chain processes and logistics is a plus.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.
• Speaking Spanish is a plus!

Requirements

• Advanced Predictive Models: Utilize machine learning algorithms to analyze historical data and identify patterns.
• Real-Time Data Integration: Incorporate real-time data into predictive models.
• Historical Data Analysis: Analyze historical data to understand common delays and their causes.
• Route Optimization: Use data analytics to identify the most efficient routes.
• Machine Learning for Anomaly Detection: Implement machine learning algorithms to detect anomalies that could affect delivery times.
• Sensor Data Utilization: Leverage data from IoT devices and sensors equipped in transportation vehicles.
• Advanced Analytics Techniques: Employ advanced analytics techniques like time series forecasting, geospatial analysis, and simulation models.

Company Description