Infocepts - Data Science Consultant

Description :

About the Role :

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

The ideal candidate will combine strong hands-on expertise in machine learning and data engineering with strategic thinking and effective stakeholder collaboration. This role requires the ability to translate complex business challenges into scalable, production-ready data science solutions.

Key Responsibilities :

Advanced Model Development & Deployment :

- Design, build, and deploy scalable machine learning and deep learning models, including :

1. Forecasting models

2. Anomaly detection systems

3. Optimization solutions

4. CNN-based models and Generative AI (GenAI) use cases

- Ensure models are production-ready, robust, and optimized for performance and scalability.

Data Engineering & Processing :

- Design and implement end-to-end data pipelines using :

1. Python and PySpark

2. Distributed computing frameworks

- Work with large, complex datasets to support advanced analytics and AI workloads.

- Ensure data quality, reliability, and performance across analytics pipelines.

Cross-Functional Collaboration :

- Partner closely with business stakeholders to understand requirements and define analytical objectives.

- Collaborate with software engineering and DevOps teams to deploy, monitor, and maintain data science solutions in production.

- Translate business problems into well-defined analytical and modeling approaches.

Governance & Responsible AI Practices :

- Ensure adherence to Responsible AI principles, including :

1. Fairness

2. Transparency

3. Explainability

4. Auditability

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

- Document model assumptions, limitations, and validation results.

Continuous Improvement & Innovation :

- Monitor model performance and data drift in production environments.

- Conduct regular evaluations and refine models to improve accuracy and reliability.

- Stay current with emerging AI/ML technologies, tools, and frameworks, and incorporate them into solutions where applicable.

Required Qualifications & Skills :

- Strong hands-on experience in data science, machine learning, and advanced analytics.

- Proficiency in Python and experience with PySpark or distributed computing frameworks.

- Experience developing and deploying ML, DL, CNN, and GenAI models.

- Solid understanding of statistical modeling, forecasting, and optimization techniques.

- Experience working with large-scale datasets and production data pipelines.

- Strong problem-solving, analytical, and communication skills.

- Ability to collaborate effectively with technical and non-technical stakeholders.