Data Scientist in Fusemachines

Fusemachines is a leading AI strategy, talent, and education services, provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

About the role:

This is a full-time remote position (contract)

We are seeking a highly skilled data scientist to join our team. The data scientist will be responsible for analyzing and interpreting complex data sets, developing predictive models, and identifying trends to help our company make informed decisions. The ideal candidate will have a strong background in statistical analysis and machine learning, with experience in data manipulation and visualization tools.

Key Responsibilities

• Analyze large, complex data sets to identify trends, patterns, and insights.
• Develop predictive models using statistical analysis and machine learning techniques, including Time Series and Churn Propensity models.
• Communicate findings to stakeholders and make recommendations based on data analysis.
• Work closely with the engineering and product teams to integrate data-driven insights into the development process.
• Collaborate with other data scientists to continuously improve our analytical capabilities and processes.
• Stay up-to-date with industry developments and emerging trends in data science.

• Bachelor's or Master's degree in computer science, statistics, mathematics, or a related field.
• Minimum of 3 years of experience in data science or a related field.
• Strong analytical and problem-solving skills with an ability to work with large, complex data sets.
• Proficient in statistical analysis and machine learning techniques, such as regression analysis, clustering, decision trees, neural networks, and deep learning.
• Experience in developing Time Series and Churn Propensity models.
• Strong programming skills in Python, R, or other programming languages commonly used in data science.
• Experience in data visualization tools, such as Tableau, PowerBI, or D3.js.
• Excellent communication skills, with an ability to clearly articulate technical concepts to both technical and non-technical stakeholders.
• Familiarity with big data technologies, such as Hadoop, Spark, and NoSQL databases is a plus.

Likely Duration

3 months