Data Science Manager

• The incumbent should have experience working with a variety of stakeholders across product engineering, sales engineering, and delivery to design and develop products aligned with the product vision and support the execution of customer-facing solutions
• He/she should also possess experience in leading a team of high-performing data scientists and overseeing their work products
• The candidate should demonstrate thought leadership, possess the ability to translate business requirements into data science problems, and provide solutions while adhering to strict timelines, budget, scope, and quality
• The candidate should be able to articulate the actionable insights drawn from cutting-edge data science models to senior leadership and business stakeholders

Professional Know-how

• Deep technical knowledge from a leading institute PhD or masters Degree in Computer Science, Data Science, or Statistics.

• Articulating a roadmap for leveraging AI across product functionality.

• Communicating to stakeholders both within and externally around the value created and changes required across other functions.

• To design, develop, and implement.

• Attend client calls and document requirements.

• Minimum 10+ years of experience in the areas of ML-based products or services.

• bachelors degree in Computer Science, Software Engineering, Data Science, or equivalent engineering degree.

• Must have excellent communication, logical reasoning, and problem-solving attitude.

• Programming Skills: Minimum 4 years of experience in Python language, with the ability to implement good quality, optimized, and complexity-based codes. Familiarity with source control and code review is preferred.

• Basic understanding and workings of DevOps and MLOps tools.

• Experienced in implementing and fine-tuning supervised and unsupervised algorithms such as classification and regression algorithms.

• Building NLP applications with a good understanding of semantic extraction, data structure, data modeling, and text representations.

• Familiarity with machine learning and deep learning frameworks such as TensorFlow and PyTorch.

• Knowledge of deep learning and computer vision algorithms, with a good understanding of neural network architectures such as CNN, LSTM, and Transformers.

• Experience with production deployments for Python REST APIs and ML models.

• Understanding of data structures, data quality, data modeling, and software architecture.

• Proficiency in handling unstructured and semi-structured data.

• Experience with data visualization tools.

• Understanding of intelligent document processing, OCRs, and ICRs.

• Hands-on experience with Cloud ML Services (GCP/AWS/Azure).

• Cloud certification(s) in Machine Learning Specialization.

• Research, develop, and implement appropriate ML algorithms and tools.

• Collaborate with multiple team members and develop ML apps.

• Research and experiment with suitable ML frameworks, algorithms, libraries, and tools