AI Data Scientist Intern

Job description

Job Summary: The AI Data Scientist will be responsible for developing, implementing, and deploying machine learning models and algorithms to extract insights and drive informed decision-making. This role requires a strong background in data science, statistics, and programming, along with the ability to collaborate with cross-functional teams.

Responsibilities:

1. Data Analysis and Exploration:
• Conduct exploratory data analysis to understand and interpret complex datasets.
• Identify patterns, trends, and anomalies in data.
2. Feature Engineering:
• Develop and engineer features from raw data to enhance model performance.
• Collaborate with domain experts to incorporate relevant features.
3. Model Development:
• Design, implement, and validate machine learning models and algorithms.
• Optimize models for performance, scalability, and interpretability.
4. Data Preprocessing:
• Clean and preprocess raw data to prepare it for model training.
• Handle missing data and outliers appropriately.
5. Model Evaluation:
• Assess model performance using appropriate metrics.
• Fine-tune models based on evaluation results.
6. Collaboration:
• Communicate findings and insights effectively to non-technical stakeholders.
7. Deployment:

• Deploy models into production environments using Cloud (Azure, AWS).

1. Continuous Improvement:
• Stay updated on the latest advancements in AI and machine learning.
• Iterate on models and algorithms for continuous improvement.

Qualifications:

1. Educational Background:
• Master’s or Ph.D. in Computer Science, Statistics, Data Science, or related field is preferred.
2. Technical Skills:
• Proficiency in programming languages such as Python, R, or others.
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch).

• Experience with data manipulation and analysis tools (e.g., pandas, NumPy).
•  Solid understanding of cloud platforms such as AWS, Azure, or Google Cloud.
• Excellent communication skills to convey complex technical concepts to non-technical stakeholders.
• Always stay updated with new advancements in the field.
• Flexible working on all types of use cases.
• Experience with time series modeling and forecasting techniques.
• Familiarity with large language models (LLM), Transformers and OpenAI.
• Knowledge of Snowflake is a plus.

1. Communication Skills:
2. Experience:
• Proven experience of 2-3 years in developing and deploying machine learning models.

Preferred:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of natural language processing (NLP) for text data.
• Experience with Snowflake.
• Experience with one of these technologies (PowerBI, QlikSense, Tableau, Streamlit)