Data Scientist
Remote
Contracted
2368446903
Mid Level
About 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 400 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
Position Overview
As a Data Scientist, you will have the opportunity to work with a wide variety of algorithms and use cases of advanced analytics that are experiencing rapid growth. Your role will involve designing, building, and validating machine learning and artificial intelligence algorithms, ranging from data exploration to training automation through MLOps. You will be part of a corporate team, providing valuable large-scale technical expertise in the company, using modern data and analytics technologies. Additionally, this position will allow you to collaborate closely with stakeholders from the business and technology sectors to establish state-of-the-art data science methodologies at the enterprise level.
Roles and Responsibilities
• Exploratory Data Analysis (EDA): Explore and analyze data to understand its structure, patterns, and relationships.
• Data Preprocessing: Clean, transform, and prepare data for further analysis.
• Predictive Modeling and Statistical Analysis: Develop predictive and analytical models to address specific business problems. Apply machine learning algorithms and advanced statistics to generate insights and accurate predictions.
• Model Evaluation: Select the most appropriate model for a given problem and evaluate its performance using relevant metrics.
• Data Visualization: Create effective visualizations to communicate findings and results to stakeholders. Use tools and techniques to graphically represent complex data.
• Model Optimization: Optimize hyperparameters and modeling techniques to improve model accuracy and performance.
• Model Validation: Perform cross-validation and other techniques to ensure model generalization and robustness.
• Model Integration: Integrate models into existing applications, systems, or processes for use in production.
• Cross-functional Collaboration: Collaborate with other teams, such as data engineers and data analysts, to implement comprehensive solutions.
• Ongoing Research and Development: Stay up-to-date with the latest trends, advances, and techniques in data science and machine learning. Research and propose new methodologies and approaches to address complex problems.
• Communication and Presentation: Communicate findings clearly and effectively to technical and non-technical audiences. Present analysis and model results to stakeholders for review and approval.
• MLOps: Collaborate with engineering teams to implement MLOps practices and ensure effective integration of models into production.
Required Skills
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 400 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.
Position Overview
As a Data Scientist, you will have the opportunity to work with a wide variety of algorithms and use cases of advanced analytics that are experiencing rapid growth. Your role will involve designing, building, and validating machine learning and artificial intelligence algorithms, ranging from data exploration to training automation through MLOps. You will be part of a corporate team, providing valuable large-scale technical expertise in the company, using modern data and analytics technologies. Additionally, this position will allow you to collaborate closely with stakeholders from the business and technology sectors to establish state-of-the-art data science methodologies at the enterprise level.
Roles and Responsibilities
• Exploratory Data Analysis (EDA): Explore and analyze data to understand its structure, patterns, and relationships.
• Data Preprocessing: Clean, transform, and prepare data for further analysis.
• Predictive Modeling and Statistical Analysis: Develop predictive and analytical models to address specific business problems. Apply machine learning algorithms and advanced statistics to generate insights and accurate predictions.
• Model Evaluation: Select the most appropriate model for a given problem and evaluate its performance using relevant metrics.
• Data Visualization: Create effective visualizations to communicate findings and results to stakeholders. Use tools and techniques to graphically represent complex data.
• Model Optimization: Optimize hyperparameters and modeling techniques to improve model accuracy and performance.
• Model Validation: Perform cross-validation and other techniques to ensure model generalization and robustness.
• Model Integration: Integrate models into existing applications, systems, or processes for use in production.
• Cross-functional Collaboration: Collaborate with other teams, such as data engineers and data analysts, to implement comprehensive solutions.
• Ongoing Research and Development: Stay up-to-date with the latest trends, advances, and techniques in data science and machine learning. Research and propose new methodologies and approaches to address complex problems.
• Communication and Presentation: Communicate findings clearly and effectively to technical and non-technical audiences. Present analysis and model results to stakeholders for review and approval.
• MLOps: Collaborate with engineering teams to implement MLOps practices and ensure effective integration of models into production.
Required Skills
- Degree in Statistics, Computer Engineering, Systems or related fields.
- Minimum of 2 years of experience in developing and implementing ML models (supervised and unsupervised).
- Knowledge of SQL Database (Intermediate Level).
- Knowledge of Python in data handling and Machine Learning libraries (supervised and unsupervised techniques, including Boosting, Random Forest, Ensembles, etc.).
- Knowledge of cloud services (AWS, GCP, etc.) for ML (Desirable).
- Good communication, organization, and business impact.
- Languages: Spoken and written English (Intermediate-advanced) and fluent Spanish.
Apply for this position
Required*