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.

Job Description:

We are seeking a Data Scientist who is passionate about leveraging data to drive impact across multiple functions. The ideal candidate will have a strong background in traditional machine learning, a solid command of Python, and SQL knowledge. Experience or familiarity with Large Language Models (LLMs) and AI techniques is a plus.
The role involves working closely with cross-functional teams to develop, implement, and optimize machine learning models, while also supporting the company’s initiatives in AI and natural language processing (NLP) advancements.

Key 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 modelling 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 but not limited to:
o	Regression models
o	Decision trees
o	Random Forests
o	XGBoost
o	SVM, etc.
•	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 (e.g., using MLOps frameworks).
•	Work with Azure to deploy models and scale data solutions.
Qualifications:
•	2-5 years of professional experience in Data Science or a related field.
•	Proficiency in Python and its data science libraries (Pandas, NumPy, Scikit-Learn, Matplotlib, etc.).
•	Strong knowledge of traditional machine learning techniques and model development.
•	Hands-on experience with SQL and relational databases (e.g., MySQL, PostgreSQL).
•	Ability to manipulate and analyze large datasets.
•	Strong problem-solving skills with the ability to find actionable insights from data.
•	Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
•	Understanding of statistical methods and how to apply them in real-world scenarios.
•	Bonus: Experience with LLMs, NLP, or AI frameworks (e.g., Transformers, OpenAI, Hugging Face).
•	Familiarity with cloud platforms (AWS, Azure, GCP) for model deployment is an added advantage.
•	Strong communication skills with the ability to explain technical results to non-technical stakeholders.
Preferred Skills:
•	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.
•	Good to know Cosmos Scope scripts.
•	Understanding of big data technologies such as Spark, Hadoop, or Databricks.
•	Exposure to cloud-based data pipelines (e.g. Azure Data Factory).