Role Objective
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
Academic:
- Deep technical knowledge from a leading institute – PhD or Master’s Degree in Computer Science, Data Science, or Statistics.
Experience:
- 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.
Working Relationships
Internal:
- To design, develop, and implement.
External:
- Attend client calls and document requirements.
Primary Responsibilities
- Minimum 10+ years of experience in the areas of ML-based products or services.
- Bachelor’s 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.
Machine Learning:
- 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.
Data:
- Understanding of data structures, data quality, data modeling, and software architecture.
- Proficiency in handling unstructured and semi-structured data.
Nice to Have:
- 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.
Competencies
- 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.
