PERSONAL SKILLS:

• You have the ability to experiment and analyze results. You are curious and eager to learn, think analytically, and work methodically. You are also enterprising and enjoy taking initiative.
• Ability to communicate technical concepts and results in an understandable way to both technical and business stakeholders.
• Ability to collaborate effectively with multiple teams and stakeholders, including analytics teams, development teams, product management, and operations. You have a constructive attitude and can connect interests.
• Experimental and entrepreneurial mindset.
• You are eager to learn and enjoy staying up-to-date with the latest (technical) developments.

TECHNICAL SKILLS:

• Expert knowledge of PyTorch, cloud services (AWS, Azure, GCP), and Python.
• Proficiency in machine learning algorithms such as multi-class classification, decision trees, support vector machines, and deep learning.
• Understanding of probability and statistical models (generative and descriptive models).
• Advanced programming experience with C/C++, Java, R, Python.
• You have experience with version control systems.

PERSONAL SKILLS:

• You have the ability to experiment and analyze results. You are curious and eager to learn, think analytically, and work methodically. You are also enterprising and enjoy taking initiative.
• Ability to communicate technical concepts and results in an understandable way to both technical and business stakeholders.
• Ability to collaborate effectively with multiple teams and stakeholders, including analytics teams, development teams, product management, and operations. You have a constructive attitude and can connect interests.
• Experimental and entrepreneurial mindset.
• You are eager to learn and enjoy staying up-to-date with the latest (technical) developments.

TECHNICAL SKILLS:

• Expert knowledge of PyTorch, cloud services (AWS, Azure, GCP), and Python.
• Proficiency in machine learning algorithms such as multi-class classification, decision trees, support vector machines, and deep learning.
• Understanding of probability and statistical models (generative and descriptive models).
• Advanced programming experience with C/C++, Java, R, Python.
• You have experience with version control systems.

Your tasks include:

• Understanding and translating business and functional needs into concrete machine learning problem statements and results.
• Designing and developing scalable machine learning and deep learning solutions that meet the organization’s needs.
• Performing data processing tasks such as normalization, feature selection, dimensionality reduction, and handling missing or outlier data.
• Working closely with data scientists, data engineers, and development teams to improve, develop, and implement machine learning algorithms.
• Translating machine learning algorithms into production-ready code.
• Evaluating model performance using cross-validation and relevant metrics.
• Monitoring implemented models, detecting data or concept drift, and updating or retraining models as needed.
• Ensuring compliance with performance standards and data security requirements.
• Continuously staying informed about new developments in machine learning and implementing them within the organization

Your tasks include:

• Understanding and translating business and functional needs into concrete machine learning problem statements and results.
• Designing and developing scalable machine learning and deep learning solutions that meet the organization’s needs.
• Performing data processing tasks such as normalization, feature selection, dimensionality reduction, and handling missing or outlier data.
• Working closely with data scientists, data engineers, and development teams to improve, develop, and implement machine learning algorithms.
• Translating machine learning algorithms into production-ready code.
• Evaluating model performance using cross-validation and relevant metrics.
• Monitoring implemented models, detecting data or concept drift, and updating or retraining models as needed.
• Ensuring compliance with performance standards and data security requirements.
• Continuously staying informed about new developments in machine learning and implementing them within the organization