At Shipday, our mission is to build better, faster local delivery infrastructure for global e-commerce. Already used in 100+ countries, our customers have processed more than 50 million deliveries on our platform.

As a rapidly growing SaaS company, we are committed to leveraging data-driven insights to drive innovation and optimize our services. We are seeking a talented and driven Data Scientist to join our dynamic team and contribute to our continued success.

As a Data Scientist at Shipday, you will play a critical role in driving insights and innovation through the analysis and interpretation of data. Your work will directly influence decision-making and strategies to improve the efficiency, effectiveness, and customer experience of our platform.

You’ll be collaborating closely with a multi-disciplinary team including engineering, product, and business development to solve complex problems and create data-driven solutions.

Who we are looking for

• Analytical and Problem Solver: You excel at analyzing data and drawing insights to solve complex problems.
• Inquisitive: You have a natural curiosity and the ability to ask the right questions to understand business needs.
• Detail-Oriented: You pay close attention to data quality and precision.
• Collaborative: You excel in a team environment and are able to communicate effectively with both technical and non-technical stakeholders.
• Results-Oriented: You focus on delivering actionable insights that have a real impact on the business.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Strong experience in data analysis and modeling.
• Proficiency in programming languages such as Python or R.
• Experience with SQL and working with large datasets.
• Familiarity with machine learning algorithms and data visualization tools.
• Strong analytical and critical thinking skills.
• Excellent communication skills to effectively convey insights and findings.

Responsibilities

• Collect, process, and clean data from various sources to create unified datasets.
• Conduct exploratory data analysis to understand trends, patterns, and outliers in the data.
• Develop predictive models and algorithms to solve business challenges.
• Communicate insights and recommendations to stakeholders through visualizations and reports.
• Collaborate with the engineering team to integrate data science models into the platform.
• Continuously monitor and evaluate the performance of models and make necessary adjustments.