Lead Data Scientist

Description:

• Machine Learning and Deep Learning:

• Design, develop, and implement state-of-the-art machine learning models and deep learning architectures to address complex business challenges.
• Utilize advanced techniques in neural networks, including convolutional and recurrent networks, to create high-performance models for a variety of applications.

• Big Data Technologies:

• Manage and analyze large-scale datasets using big data technologies and architectures, ensuring efficient processing and storage solutions.
• Optimize data pipelines and workflows to handle complex data structures and enhance overall data accessibility.

• Model Tuning and Optimization:

• Conduct thorough model tuning and optimization to enhance performance, accuracy, and efficiency.
• Employ advanced techniques for model performance evaluation, including cross-validation, hyperparameter tuning, and error analysis.

• Data IQ and Workflow Automation:

• Leverage Data IQ to manage and automate data science workflows, including model development, deployment, and monitoring.
• Implement best practices for model management, versioning, and continuous integration/continuous deployment (CI/CD).

• AI and ML Strategy:

• Develop and implement AI and ML strategies aligned with organizational goals and objectives.
• Collaborate with cross-functional teams to integrate AI and ML solutions into business processes and drive data-driven decision-making.

• Natural Language Processing (NLP):

• Apply advanced NLP techniques for text analytics, sentiment analysis, and language understanding.
• Develop and deploy models for extracting insights and patterns from unstructured text data.

• Graph Databases and Network Analysis:

• Utilize graph databases and network analysis techniques to model and analyze relationships and interactions within complex data structures.
• Develop solutions for network-based insights and predictions.

• Cloud Platforms:

• Utilize cloud platforms (AWS, GCP, Azure) to deploy and scale data science solutions, ensuring robust and scalable infrastructure.
• Manage cloud-based data storage, compute resources, and security to support large-scale data science operations.

Qualifications:

• Education: Bachelor Degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Experience: 7+ years of experience in data science, machine learning, and big data technologies, with a proven track record of successful project delivery.
• Technical Skills:
• Deep expertise in machine learning algorithms and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Proficiency in big data technologies (e.g., Hadoop, Spark, Kafka).
• Advanced skills in model tuning, optimization, and performance evaluation.
• Expertise in NLP and advanced text analytics techniques.
• Experience with graph databases and network analysis.
• Proficiency in cloud platforms (AWS, GCP, Azure) and associated data science tools.
• Strong programming skills in Python, R, SQL, and other relevant languages.