Data Scientist

You will be responsible for analyzing large datasets and uncovering valuable business insights through data mining techniques. You will develop and deploy predictive models for various applications such as customer segmentation, demand forecasting, and anomaly detection. Collaboration with cross-functional teams to understand business requirements and translate them into technical solutions will be a key aspect of your role. Designing and implementing data-driven models to ensure scalability, efficiency, and accuracy is also part of your responsibilities. You will be required to perform data preprocessing and feature engineering to prepare data for analysis. Continuously monitoring, evaluating, and optimizing deployed models to improve performance will be essential. Staying current with the latest developments in machine learning and data science to implement best practices is expected. Presenting findings and recommendations clearly to both technical and non-technical stakeholders is also part of the job. To be a great fit for this role, you should have 3-7 years of experience in data science or a related role. Proven expertise in building, training, and deploying machine learning models is crucial. A solid understanding of statistical techniques, machine learning algorithms (supervised, unsupervised learning), and deep learning is required. Proficiency in Python and hands-on experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn is necessary. Strong problem-solving skills with the ability to work with large, complex datasets are also important. Excellent communication and collaboration skills to work effectively with technical and non-technical teams are a must. Experience with cloud platforms (AWS, GCP, Azure), familiarity with big data technologies (e.g., Hadoop, Spark), experience with MLOps tools and workflows, and knowledge of data visualization tools like Tableau or Power BI are considered bonus points for this role.,