Accenture Data Science Job Openings 2025

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
• Experience: 1-5 years in data science
• Must have skills: Gen AI / ML, SQL, Python, Azure / AWS, ML Ops
• Good to have skills: Experience in data science projects focused on Utilities, Oil & Gas, Mining, Manufacturing, Chemicals and Forest Product

Technical Skills:

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

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.

Job Summary & Responsibilities:

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.

1.Data Science and Engineering

• Perform advanced analytics using Python, SQL, Pyspark using 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

2.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.

3.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.

4.Generative AI Expertise

• Lead the development of Generative AI based application 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.