Sr. Data Scientist/Machine Learning Engineer with LLM

Must Have: Strong exp in LLM models with ChatGPT and OpenAI

What You Will Do

Partner with business stakeholders to gather requirements and translate them into technical specifications and process documentation for IT counterparts.

Conduct exploratory data analysis to identify patterns, anomalies, and relationships within the data.

Generate summary statistics and visualizations to provide insights into the data's characteristics.

Apply statistical techniques to test hypotheses and validate models.

Perform regression analysis, hypothesis testing, and other statistical methods to extract actionable insights.

Develop and train machine learning models to solve specific business problems (e.g., classification, regression, clustering etc.).

Build predictive models to forecast future trends, such as demand forecasting, customer behaviour prediction, product recommendation etc.

Evaluate model performance using appropriate metrics and validate results with cross-validation techniques.

Select appropriate algorithms and optimize model performance through hyperparameter tuning.

Develop, fine-tune, and deploy Large Language Models for various applications such as text generation, sentiment analysis, and information retrieval.

Integrate LLMs into existing data pipelines and business processes.

Develop custom algorithms and tools to address specific business challenges.

Continuously improve/fine tune existing models and algorithms based on new data and feedback loops.

Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence.

Experiment with new techniques and technologies to enhance analytical capabilities.

Education Qualifications

Bachelor's Degree or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Experience Qualifications

5+ years of experience working in Data science roles operational environments or business consulting organizations.

Working knowledge of large data set manipulation using SQL.

Hands-on experience with state-of-the-art LLMs such as GPT-3, GPT-4, BERT, T5, etc.

Skills And Abilities

Proficiency in programming languages commonly used in machine learning such as Python. Should be comfortable with libraries like TensorFlow, PyTorch, scikit-learn, or Keras.

Understanding of statistical concepts and techniques is essential for data preprocessing, model evaluation, and interpretation of results.

Ability to manipulate and preprocess data efficiently using libraries like pandas for data manipulation and NumPy for numerical operations.

Familiarity with various machine learning algorithms including supervised and unsupervised learning methods like regression, classification, clustering, and dimensionality reduction etc.

Good understanding of deep learning architectures such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their applications

Strong analytical and problem-solving skills to approach real-world challenges and devise effective solutions using machine learning techniques.

Ability to communicate effectively, both verbally and in writing, to convey complex technical concepts to non-technical stakeholders and collaborate within a team environment.

Exposure to reporting tools using Tableau.