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Accenture

Advises businesses and runs their technology

Senior Data Scientist - Data & AI

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A bachelor's degree or higher in Computer Science, Mathematics, Statistics, Data Science, or another relevant technical field is required.
  • At least 4 years of professional experience in Data Science, Machine Learning, Data Engineering, or a closely related area is required.
  • Strong hands-on skills in Python and PySpark, including data wrangling, feature engineering, distributed processing, and working with large-scale datasets are required.
  • Knowledge of machine learning, predictive modeling, statistics, and probability, with experience using libraries or frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow, is required.
  • Practical MLOps experience, including experiment tracking tools such as MLflow or Weights & Biases and CI/CD for machine learning models, is required.
  • Strong experience with cloud platforms such as AWS, Azure, or GCP for model deployment and data processing is required.
  • Experience working directly with external clients, gathering and translating business requirements into analytical objectives, and communicating analytical findings and actionable recommendations is required.
  • Understanding of Responsible AI, including model fairness, explainability, and bias mitigation, and knowledge of LLMs and Generative AI and their application to analytical use cases, is required.
  • Proficiency with AI-assisted development tools such as Cursor, Copilot, or similar solutions is required.
  • Fluent English at a minimum C1 level is required.

Responsibilities

  • Design and develop machine learning and predictive analytics solutions, select suitable modeling approaches, and rigorously validate results.
  • Work directly with clients to understand business needs, translate them into analytics objectives, communicate findings, and recommend actions that create business value.
  • Build scalable analytical solutions using Python, PySpark, cloud platforms, and machine learning frameworks; work with large datasets and apply feature engineering and statistical methods.
  • Apply MLOps practices, experiment tracking, model deployment, CI/CD, Responsible AI principles, and model explainability.
  • Explore how LLMs and Generative AI can support analytics use cases such as Text-to-SQL, data summarization, and conversational analytics.

Desired Qualifications

  • Experience with Databricks and building NLP solutions or processing text data at scale.
  • Hands-on experience with RAG pipelines, embeddings, or vector databases in analytical use cases.
  • Experience with visualization solutions such as Power BI, Tableau, or Streamlit; containerization and API tooling such as Docker, FastAPI, or Flask; or contributions to open-source projects, research, or Kaggle competitions.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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