Infocepts - Data Science Consultant - Machine Learning

Role Summary :

We are seeking an experienced Data Science Consultant to lead the design, development, and deployment of advanced data science and AI solutions across multiple business domains. This role focuses on delivering measurable business impact through forecasting, optimization, anomaly detection, and AI-driven innovation.

The ideal candidate will combine strong hands-on technical expertise, strategic problem-solving, and effective stakeholder collaboration to build scalable, production-ready data science solutions aligned with organizational goals.

Key Responsibilities :

Advanced Model Development & Deployment :

- Design, build, and deploy machine learning, deep learning, and Generative AI models for use cases such as anomaly detection, demand forecasting, optimization, and predictive analytics.

- Develop and productionize models using techniques including CNNs, traditional ML algorithms, and GenAI frameworks.

- Evaluate model performance, perform tuning, and ensure scalability and reliability in production environments.

Data Engineering & Processing :

- Design and implement robust data pipelines using Python, PySpark, and distributed computing frameworks.

- Work with large, complex datasets to enable high-performance analytics and model training.

- Ensure data quality, reliability, and efficiency across end-to-end data workflows.

Cross-functional Collaboration :

- Partner with business stakeholders, software engineers, and DevOps teams to understand requirements and translate them into actionable data science solutions.

- Support solution design discussions and provide technical guidance throughout the delivery lifecycle.

- Communicate complex analytical insights clearly to both technical and non-technical audiences.

Governance & Responsible AI :

- Ensure adherence to Responsible AI principles, including fairness, transparency, explainability, and auditability.

- Comply with enterprise data governance, security, and compliance standards.

- Document models, assumptions, and decision logic for audit and regulatory requirements.

Continuous Improvement & Innovation :

- Monitor deployed models, analyze performance drift, and continuously improve accuracy and robustness.

- Stay current with emerging AI/ML technologies, tools, and best practices, and integrate them into solutions.

- Contribute to innovation initiatives and development of reusable analytics components.

Required Skills & Qualifications :

- Strong hands-on experience in Data Science, Machine Learning, and Advanced Analytics.

- Proficiency in Python and experience with PySpark and distributed data processing.

- Experience developing and deploying ML, Deep Learning, and GenAI solutions.

- Solid understanding of statistical modeling, feature engineering, and model evaluation techniques.

- Experience working with large datasets and enterprise data platforms.

- Strong problem-solving, communication, and stakeholder management skills.

Preferred/Good to Have :

- Experience with cloud platforms (AWS, Azure, or GCP).

- Exposure to MLOps practices, model monitoring, and CI/CD pipelines.

- Experience in forecasting, optimization, or operational analytics use cases.

- Familiarity with AI governance, explainability frameworks, and Responsible AI standards.