Data Scientist (AI/ML)

We are seeking a talented AI/ML Engineer with a strong foundation in both supervised and unsupervised learning techniques. The ideal candidate will be responsible for experimenting with and optimizing various machine learning models to solve predictive analytics, decision support, and forecasting challenges. You will work in a collaborative environment to design, refine, and deploy scalable models that meet evolving business needs.

Key Responsibilities:

  • Develop and implement machine learning models to solve complex business problems.
  • Build scalable pipelines for data ingestion, preprocessing, model training, and deployment.
  • Ensure solutions are robust, reliable, and production-ready.
  • Data Analysis and Feature Engineering
  • Perform in-depth data analysis to uncover patterns and insights.
  • Engineer features to improve model accuracy and performance.
  • Work with large, diverse datasets to identify actionable insights.
  • Algorithm Design and Optimization
  • Experiment with and optimize supervised and unsupervised learning techniques.
  • Implement algorithms for predictive analytics, forecasting, and decision support.
  • Continuously refine models based on feedback and evolving requirements.
  • Collaboration and Communication
  • Stay updated with advancements in AI/ML research and integrate relevant techniques into projects.
  • Monitor deployed models and refine them for performance and scalability.
  • Advocate for best practices in machine learning and ethical AI usage

Skills Required:


Proficiency in programming languages such as Python or R.

3+ years of hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).

Knowledge of data handling tools and techniques, including SQL, ETL processes, and big data tools (e.g., Spark, Hadoop).

Experience with traditional ML

Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Experience with ML algorithms and Deep learning algorithms.

Preferred Qualifications:

Knowledge of optimization techniques and decision-support algorithms.

Exposure to A/B testing and performance evaluation frameworks.

Strong problem-solving skills and ability to work in fast-paced environments