AI/ML Computational Science Analyst

Skill required: Data Scientist - Data Science

Designation: AI/ML Computational Science Analyst

**Qualifications:**Post Graduate diploma in Statistics

**Years of Experience:**3 to 5 years

What would you do

• Intelligent Operations centers. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. .
  We provide BPO services to client operations in 150 countries and 45+ languages and provide infrastructure services to clients in 49 countries and 20 languages. We have our market leading 10 focus offerings in business process outsourcing (F&A, Marketing, Talent & HR, Supply Chain, Procurement, Network, Life Sciences, Utilities, Credit Services, Health Admin and Care Management) and leading infrastructure service offerings in infrastructure consulting, infrastructure management, cloud and security.
  Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases, and engaging in fundamental research to develop novel solutions. They also leverage the vast global network of Accenture to collaborate with Accenture Tech Labs, Accenture Open Innovation and Accenture Analytics for creating solutions.

  Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced analytics projects from design to execution.

• Minimum 1 to 3 years of industry experience in fields like Financial Services, Capital Markets, Healthcare, Pharmaceuticals, and Retail, with hands-on expertise in making data-driven decisions

• Proficient in statistical tools and languages, including Python/R, and Alteryx

• Familiarity with the visualization tools like Tableau, PowerBI, Google Data Studio, Qlik and visualization packages such as R-Shiny, Django, Streamlit, DASH, tkinter

• Familiarity with relational databases and intermediate level knowledge of SQL

• Excel and data related applications like analysis tool pack

• Hands-on experience in data science, including developing and deploying machine learning models for production environments

• Proficiency with large datasets and tools such as MapReduce, Hadoop, and Hive

• Familiarity with non-relational databases like MongoDB

• Experience with large data streaming technologies like Spark and Flink

• Experience in one or more domains: Infrastructure Services, Security, Retail, Digital Marketing, eCommerce, Healthcare, Supply Chain, Banking

• Excellent written and verbal communication skills in English

• Ability to think creatively to solve real world business problems

• Multivariate Statistics such as Regression Analysis, Logistic Analysis, PCA, Factor Analysis, Cluster Analysis, Generalized Linear Mixed Models, Linear Mixed Effects Model

• Supervised and Unsupervised learning such as Random Forest, Gradient Boosting Machines, Decision Tree, SVM, KNN, k-Means Clustering, DBSCAN

• Forecasting techniques such as ARIMA/SARIMA/ARIMAX, LSTM, GRU, Prophet, Ensemble Methods, Bayesian Structural Time Series

• Boosting Algorithms such as Gradient Boosting Machines (GBM), XGBoost, LightGBM, Adaboost, CatBoost

• NLP/Text Analytics such as NLP, Text Mining, Sentiment Analysis, Document Clustering, Chatbot

• Deep learning techniques such as ANN, CNN, LSTM, RNN, Sequence to Sequence Model, Transformer Network

• GenAI such as Gemini, BERT, Reinforcement Learning, OpenAI, GPT

• Simulation methods such as Montecarlo, Discrete, Agent-based, System-Dynamic

• Optimization methods such as Integer, Linear, Non-Linear Programming, Transport Optimization, Networking & Scheduling Problem

• Machine Learning tools such as PyTorch, TensorFlow, Keras

• Cloud-based computing platforms such as AWS, GCP, Azure DB

• Proficient in Excel VBA

• In this position, you will analyze and resolve lower-complexity issues, primarily interacting with peers at Accenture before reporting to supervisors

• Your interactions may be limited with clients or Accenture management

• You will receive required guidance on daily tasks and detailed instructions for new assignments

• Your decisions will influence your own work and potentially that of others

• This role involves individual contribution within a team environment, focusing on specific tasks. Rotational shifts may be required