Job Description

• Develop and implement machine learning models. Improve model accuracy through iterative testing.

• Utilize supervised, unsupervised, reinforcement, and deep learning techniques.

• Design and create features for data science applications.

• Integrate and monitor AI models. Apply NLP, computer vision, and predictive analytics.

• Perform data preprocessing and transformation. Ensure data quality and integrity.

• Implement ETL processes and data warehousing.

• Use advanced data techniques and big data technologies.

Additional Responsibilities: 

• Collaboration: Work closely with cross-functional teams, including data scientists, data engineers, and business analysts, to deliver comprehensive solutions.

• Documentation: Maintain thorough documentation of models, features, and data engineering processes.

• Innovation: Proactively identify opportunities for innovation and improvement in data science.

Skills Required: 

• Proficiency in programming languages such as Python, PySpark, and SQL.

• Experience with machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn.

• Knowledge of AI techniques including NLP, computer vision, and reinforcement learning.

• Expertise in data engineering tools and platforms such as Apache Kafka, Airflow, and MS Azure.

• Strong understanding of data structures, algorithms, and software development principles.

• Ability to work with large datasets and perform complex data analysis.

• Proficiency in Power BI for data visualization and reporting