The Data Science Consultant will lead the design, development, and deployment of advanced data science solutions across business domains, with a strong focus on operational efficiency, forecasting, and AI integration. This role demands a blend of technical expertise, strategic thinking, and stakeholder collaboration to deliver measurable business impact through data-driven innovation.
Key Result Areas and Activities:
Advanced Model Development & Deployment:
Build and deploy scalable machine learning and deep learning models (including CNNs and GenAI solutions) for anomaly detection, forecasting, and optimization.
Data Engineering & Processing:
Design and implement efficient data pipelines using Python, PySpark, and distributed computing frameworks to support large-scale analytics.
Cross-functional Collaboration:
Work closely with business stakeholders, software engineers, and DevOps teams to translate business needs into actionable data science solutions.
Governance & Responsible AI Practices:
Ensure models adhere to responsible AI principles including fairness, transparency, and auditability, and comply with data governance standards.
Continuous Improvement & Innovation:
Monitor model performance, conduct evaluations, and iterate to improve accuracy and reliability. Stay abreast of emerging AI/ML technologies and integrate them into solutions.
Essential Skills:
Strong proficiency in Python and PySpark for data manipulation and modeling.
Experience with deep learning frameworks such as TensorFlow and PyTorch.
Hands-on experience with CNNs and other advanced ML techniques for forecasting and anomaly detection.
Expertise in building and deploying models in production environments.
Familiarity with distributed computing tools (e.g., Spark, Databricks).
Knowledge of AI governance and responsible AI frameworks.
Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
Desirable Skills:
Experience with GenAI platforms and LLMOps tools (e.g., LangChain, MLflow).
Understanding of vector databases and RAG pipelines.
Exposure to CI/CD pipelines and DevOps practices.
Ability to conduct market research and contribute to product strategy.
Experience in supply chain or operations domain analytics.
Qualification:
Experience:
Overall 11 years of experience, including a minimum of 7+ years in data science, machine learning, or AI development, with proven expertise in deploying solutions at scale.
Education:
Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field.
Qualities:
Strong analytical and strategic thinking.
Excellent communication and stakeholder management.
Leadership and mentoring capabilities.
Adaptability in dynamic and multicultural environments.
Passion for innovation and continuous learning.
Years Of Exp
11 to 14 years
Location
Nagpur
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