Job Description

Accenture Applied Intelligence practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition


As part of our Analytics practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically-informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance.

Analyst/Consultant in Applied Intelligence

A data science analyst/consultant in Applied Intelligence understands the importance of sound analytical decision-making, the relationship of tasks to the overall project, and executes projects in the context of a business performance improvement initiative. This role combines hands-on model development with leadership responsibilities, translating business problems into measurable outcomes, ensuring data quality, scalable solutions, and actionable insights for stakeholders.

Duties and Responsibilities:

Define data requirements aligned with business objectives and success metrics. Clean, aggregate, and analyze data; conduct quality checks and exploratory analysis. Prepare datasets for modeling; document assumptions, lineage, and transformations. Engineer features and develop statistical, econometric, ML, and NLP/GenAI models (LLMs, embeddings, RAG pipelines). Evaluate models for performance, explainability, and fairness. Design, build, and deploy scalable AI/ML solutions in Python using AWS/GCP/Azure with MLOps/LLMOps (versioning, CI/CD, monitoring, governance). Utilize modern LLMs (e.g., GPT, BERT, Llama) for NLP tasks such as text generation, semantic search, summarization, and conversational agents. Architect autonomous multi-agent systems for business process automation. Transform research and prototypes into robust, production-ready systems following software engineering best practices. Monitor, troubleshoot, and optimize deployed models and agents for performance and reliability. Partner with managers and leadership to convert insights into actionable recommendations and executive presentations. Lead small project pods, review code, and enforce standards and best practices. Collaborate with cross-functional teams to translate business needs into AI solutions. Contribute to proprietary assets (feature stores, prompt libraries, evaluation harnesses).

Document solution architectures, workflows, and technical decisions

Educational Background/qualifications

B.Tech/M.Tech from reputed engineering colleges; or Master's in Computer Science, Statistics, Econometrics, or Economics from a reputed institute.

Requirements:

1-8 years of experience in analytics or data science projects Strong statistical modeling, customer analytics, segmentation, NLP, and GenAI skills. Proficiency in regression analysis, hypothesis testing, multivariate analysis, time series, optimization, and ML algorithms (Random Forest, Gradient Boosting, Neural Networks). Hands-on experience with Python, R, Spark, and ML/NLP frameworks (scikit-learn, PyTorch, TensorFlow, Hugging Face). Hands-on experience with Prompt Engineering, creating RAG pipelines and building agents in different frameworks such as Crew.AI or LangGraph etc. Familiarity with cloud data platforms (AWS, Azure, GCP) and MLOps/LLMOps workflows. Experience in leading teams will be a plus

Soft Skills

Strong analytical skills Good team player Attention to details Good communication skills

Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.