What are the responsibilities and job description for the Data Scientist (AI & ML Specialist) - to 220k + bonus + equity position at Phaxis?
Salary is 180k to 220k bonus equity
Hybrid position
Seeking an experienced and highly skilled Data Scientist with expertise in Artificial Intelligence (AI), Machine Learning (ML), and Python programming to join our team. The ideal candidate will have a strong background in data analysis, algorithm development, and statistical modeling, with a focus on implementing AI / ML solutions to solve complex business problems. You will work closely with cross-functional teams to design, build, and deploy scalable data-driven models and insights that drive innovation and business success.
Key Responsibilities :
- Data Analysis and Preprocessing :
- Collect, clean, and preprocess large datasets from various sources.
- Perform exploratory data analysis (EDA) to uncover trends, patterns, and anomalies.
- Develop and optimize data pipelines for efficient data handling and transformation.
- Machine Learning and AI Model Development :
- Design, develop, and deploy machine learning models using a variety of algorithms such as regression, classification, clustering, and deep learning techniques.
- Implement AI solutions to automate and optimize business processes.
- Fine-tune models for better accuracy, efficiency, and scalability.
- Algorithm Development and Optimization :
- Build and optimize algorithms to handle large-scale data and improve model performance.
- Leverage advanced machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar tools to implement state-of-the-art models.
- Python Programming and Software Development :
- Write clean, efficient, and scalable Python code for data analysis and model development.
- Utilize libraries such as Pandas, NumPy, SciPy, and others to perform data manipulation and analysis.
- Integrate AI / ML models with existing software infrastructure and deploy them in production environments.
- Model Evaluation and Validation :
- Evaluate model performance using appropriate metrics (e.g., accuracy, precision, recall, F1 score).
- Conduct model validation to ensure robustness, reliability, and generalizability of solutions.
- Collaboration and Reporting :
- Work closely with business leaders, engineers, and other stakeholders to translate business requirements into AI / ML solutions.
- Present findings and model results to non-technical stakeholders in a clear and actionable manner.
- Create and maintain documentation for processes, models, and methodologies.
Requirements :
Preferred Skills :
