1. Job Title: Data Scientist  
2. Introduction/Overview: We are a dynamic and growing organization that leverages data to drive decision-making and innovation, our team is focused on solving complex business problems by utilizing advanced analytics, machine learning models, and AI-driven solutions, we encourage a collaborative environment where creativity and learning are at the heart of our success.  
3. Roles & Responsibilities: Develop, test, and deploy machine learning models to solve complex business problems such as prediction, classification, and clustering tasks, work experience in causal inference modeling is a big advantage, perform data cleaning, transformation, and feature engineering to prepare datasets for modeling, analyze large, diverse datasets using Python libraries like Pandas, NumPy, Scikit-Learn, and others, write complex SQL queries to extract, manipulate, and analyze data from relational databases, build and evaluate predictive models including regression models, decision trees, random forests, XGBoost, and SVM, develop, validate, and optimize classification models (binary, multi-class), monitor and enhance model performance using metrics like precision, recall, AUC, and accuracy, collaborate with data engineers, business analysts, and stakeholders to ensure alignment of models with business objectives, communicate insights and findings to stakeholders through data visualizations and reports, stay up to date with advancements in AI and LLM technologies to explore new possibilities for NLP, chatbots, and generative AI in the business, implement best practices for model management, versioning, and deployment using MLOps frameworks, work with Azure to deploy models and scale data solutions.  
4. Years of Experience: 2-5 years of professional experience in Data Science or a related field.  
5. Education Qualification: No Details Found.  
6. Skills/Knowledge: Proficiency in Python and its data science libraries including Pandas, NumPy, Scikit-Learn, and Matplotlib, strong knowledge of traditional machine learning techniques and model development, hands-on experience with SQL and relational databases such as MySQL and PostgreSQL, ability to manipulate and analyze large datasets, familiarity with data visualization tools such as Tableau, Power BI, Matplotlib, and Seaborn, understanding of statistical methods and their real-world applications, experience with LLMs, NLP, or AI frameworks such as Transformers, OpenAI, and Hugging Face is a plus, familiarity with cloud platforms including AWS, Azure, and GCP for model deployment, strong communication skills to explain technical results to non-technical stakeholders, familiarity with deep learning frameworks like TensorFlow or PyTorch, experience in MLOps for model deployment, scaling, and management, hands-on experience with LLMs, Generative AI, or natural language processing techniques, knowledge of Cosmos Scope scripts, understanding of big data technologies such as Spark, Hadoop, or Databricks, exposure to cloud-based data pipelines such as Azure Data Factory.  
7. Key Competencies: Strong problem-solving skills with the ability to find actionable insights from data, ability to work collaboratively with cross-functional teams, effective communication skills to convey technical insights to stakeholders, adaptability to stay updated with advancements in AI and machine learning, ability to implement best practices for model management and deployment.  
8. Domain/Industry: No Details Found.  
9. Employment Type: No Details Found.  
10. Company Overview: No Details Found.  
11. Benefits & Opportunities: No Details Found.  
12. Location & Travel: No Details Found.