Key Responsibilities :

- Design and implement machine learning models to solve business problems, improving accuracy and efficiency for our clients.

- Develop and maintain data pipelines to ensure data quality and availability for analytical projects, enabling timely and reliable insights.

- Conduct exploratory data analysis and data mining to identify trends and patterns, informing strategic business decisions for our clients.

- Create compelling data visualizations and dashboards to communicate insights to stakeholders, facilitating data-driven decision-making.

- Collaborate with data engineers to build scalable and robust data infrastructure, supporting the growing data needs of our clients.

- Evaluate and implement new data science techniques and technologies, keeping our solutions at the forefront of innovation.

- Present findings and recommendations to clients, influencing their strategies and driving tangible business outcomes.

Required Skillset :

- Demonstrated ability to develop and deploy machine learning models using Python and related libraries (e.g., scikit-learn, TensorFlow, PyTorch).

- Proven experience in data mining, data modeling, and data visualization techniques to extract meaningful insights from large datasets.

- Strong proficiency in SQL and experience working with relational databases to access and manipulate data.

- Hands-on experience with Big Data technologies such as Hadoop and Spark for processing and analyzing large-scale datasets.

- Excellent communication and presentation skills to effectively convey complex technical concepts to both technical and non-technical audiences.

- Ability to work independently and collaboratively in a fast-paced, client-focused environment.

- A Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.