Data Science Analyst

About the Role

We are seeking a highly skilled and motivated Data Science Analyst to work on innovative projects and drive impactful solutions in domains such as Utilities, Oil & Gas, Mining, Manufacturing, Chemicals and Forest Product. This role requires hands-on technical expertise and client delivery management skills to execute cutting-edge projects in Generative AI, data science, and cloud-based analytics.

Key Responsibilities

• Data Science and Engineering
• Perform advanced analytics using Python, SQL, Pyspark with machine learning frameworks.
• Develop predictive models, recommendation systems, and optimization solutions tailored to business needs.
• Manage and preprocess large, complex datasets, ensuring efficient pipelines and advanced feature engineering across structured and unstructured data.
• Build MLOps pipelines for model training/retraining, monitoring, and scalability.
• Dashboard and Reporting
• Develop dashboards, reports, and insights to track the impact of deployed models on business outcomes in PowerBI/Tableau.
• Present results and recommendations to stakeholders, leveraging data storytelling to drive decision-making.
• Cloud Platform Expertise
• Design and implement end-to-end data science workflows on cloud platforms (e.g., AWS, Azure, GCP) for business-critical projects.
• Leverage cloud-native tools and services (e.g., Databricks, ADF, Lambda, Glue, AzureML) for training, deploying, and monitoring machine learning models at scale.
• Generative AI Expertise
• Lead the development of Generative AI-based applications and solutions leveraging frameworks like LangChain, LlamaIndex.
• Drive model evaluation strategies using advanced metrics (e.g., BLEU, ROUGE, FID) and iteratively optimize performance for production-grade applications.
• Architect deployment solutions, including API development and seamless integration with existing systems.

Requirements & Tech Stack

• Must-have skills: Gen AI / ML, SQL, Python, Azure / AWS, ML Ops
• Programming: Proficiency in Python, SQL and Pyspark.
• GenAI Expertise:
• Hands-on experience in building GenAI-based applications and solutions.
• Experience in deploying GenAI applications in production.
• Cloud Platforms: Experience with Azure / AWS / GCP.
• Visualization Tools: PowerBI / Tableau.

Qualifications

• Education: Bachelor's / Master's degree in Computer Science, Statistics, Applied Mathematics, or a related field.
• Industry Knowledge: Preferred experience in Utilities, Oil & Gas, Mining, Manufacturing, Chemicals and Forest Product.
• Preferred Skills:
• Strong analytical and problem-solving skills with a results-oriented mindset.
• Good communication and stakeholder management capabilities.
• Very good in generating business insights and presenting to stakeholders.