Sr Data and ML Scientists

HRB; Canada; Remote; CAD 70,000 - 110,000; Full time

Job summary

An innovative firm is seeking a skilled Data Scientist to enhance supply chain solutions through advanced analytics and machine learning. In this role, you will collaborate with a talented team to develop predictive models and data pipelines that provide real-time insights and optimize processes. Your expertise will be pivotal in transforming complex data into actionable strategies, ensuring efficiency and accuracy in supply chain operations. This position offers a unique opportunity to work with cutting-edge technology and contribute to impactful projects in a dynamic environment. If you're passionate about data and eager to make a difference, this role is perfect for you.

Qualifications

• 5+ years experience in machine learning and statistical modeling.
• Proficiency in Python or R and SQL for data manipulation.
• Strong problem-solving and analytical skills.

Responsibilities

• Develop machine learning models to enhance supply chain ETAs.
• Analyze datasets to extract insights and identify trends.
• Design scalable data pipelines for efficient data flow.

Skills

Machine Learning

Statistical Modeling

Data Analysis

Python

R

SQL

Data Visualization

Problem-Solving

Communication

Education

BS in Data Science

MS in Data Science

BS in Statistics

BS in Computer Science

Tools

Data Lakes

Data Pipelines

IoT Devices

Job description

POSITION OVERVIEW

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.

What You Will Do

• 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.

Key Responsibilities

1. Advanced Predictive Models: Utilize machine learning algorithms to analyze historical data and identify patterns. Models such as regression analysis, neural networks, or ensemble methods can predict ETAs more accurately by considering various factors like traffic conditions, weather, route efficiency, and historical performance.
2. Real-Time Data Integration: Incorporate real-time data into predictive models, including traffic updates, weather conditions, vehicle speed, and location data. This allows for dynamic adjustments to ETA predictions as conditions change.
3. Historical Data Analysis: Analyze historical data to understand common delays and their causes, helping to adjust predictive models accordingly.
4. Route Optimization: Use data analytics to identify the most efficient routes, shortening travel time and improving ETA reliability.
5. Machine Learning for Anomaly Detection: Implement algorithms to detect anomalies affecting delivery times, such as traffic jams or vehicle breakdowns, and adjust ETAs.
6. Sensor Data Utilization: Leverage data from IoT devices and sensors in transportation vehicles to gain insights into vehicle performance and road conditions.
7. Advanced Analytics Techniques: Employ time series forecasting, geospatial analysis, and simulation models to enhance ETA predictions.

Skills, Knowledge, and Expertise

We value diversity and encourage all interested candidates, regardless of whether they meet all qualifications, to apply. While the following qualifications are relevant, they are not strict requirements:

• BS or MS degree in Data Science, Statistics, Computer Science, or a related field.
• Proven experience in machine learning and 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!
• We prioritize employees located in the Eastern Time Zone (NYC) and CET (Amsterdam) for regular team sessions.