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).