Job Summary:
As a Data Scientist at Neo Garden, you will be a key player in the development and implementation of AI models that will optimize various aspects of our catering services. You will work collaboratively with cross-functional teams to extract insights from data, build predictive models, and drive data-driven decision-making processes.
Key Responsibilities:
Data Analysis and Exploration:
- Collaborate with business stakeholders to understand data requirements and identify opportunities for AI application.
- Analyze large datasets to derive meaningful insights that contribute to business strategy and decision-making.
Model Development and Implementation:
- Design, develop, and implement machine learning models and algorithms to address business challenges and improve operational efficiency.
- Optimize and fine-tune models for enhanced performance and accuracy.
Data Integration:
- Work with the IT team to integrate AI models into existing systems, ensuring seamless functionality and real-time data processing.
- Collaborate with data engineers and data analysts to optimize data pipelines for model deployment.
- Enhance data collection procedures to include all relevant information for developing analytic systems
Validation and Testing:
- Conduct thorough testing and validation of models to ensure accuracy, reliability, and robustness.
- Monitor and analyze model performance, adjusting as necessary to maintain optimal results.
Collaboration and Communication:
- Collaborate with cross-functional teams, including technology, marketing, and operations, to understand business needs and align AI initiatives accordingly.
- Communicate complex technical concepts and findings to non-technical stakeholders clearly.
Qualifications:
- Proven experience as a Data Scientist, with a focus on machine learning and AI applications.
- Strong programming skills in languages such as Python or R.
- Experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Familiarity with data visualization tools and techniques.
- Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
- Problem-solving aptitude
- Solid understanding of statistical concepts and methodologies.
Education and Experience:
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
- Minimum of 2 years of experience in data science or related roles.
