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Accenture

Advises businesses and runs their technology

AI / ML Engineer

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

About the Job

Requirements

  • At least 7.5 years of experience is required; additional information specifies a minimum of 8 years in Data Science.
  • 15 years of full-time education is required.
  • Experience in Data Science, machine learning, Python frameworks, and MySQL is required.
  • Strong experience with traditional machine learning techniques, including regression, classification, and statistical modeling, is required.
  • Strong Python and SQL skills and hands-on experience building and validating predictive models are required.
  • Strong analytical thinking is required.
  • Candidates should have solid understanding of statistics and probability, including distributions, hypothesis testing, variance, and confidence intervals.
  • Hands-on experience with machine learning algorithms including logistic regression, linear regression, and tree-based models such as random forest, gradient boosting, and XGBoost is required.
  • Experience with model validation techniques, including cross-validation and train-test strategies, is required.
  • Experience with hyperparameter tuning approaches, including grid search, random search, and Bayesian optimization, is required.
  • Experience with data cleansing, transformation, and feature engineering is required.
  • Understanding of algorithms and data structures fundamentals, including sorting, searching, and basic graph concepts, is required.
  • Experience with Databricks, Apache Spark, or PySpark is required.
  • Experience building and deploying inference or prediction pipelines is required.
  • Availability to provide Shift B support until 11 AM PST is required.
  • Availability for mandatory five-day return-to-office work at one of the listed strategic office locations is required.

Responsibilities

  • Develop, train, and deploy machine learning models for classification, regression, and predictive analytics use cases.
  • Perform data exploration, preprocessing, and feature engineering on large and complex datasets.
  • Apply statistical techniques, including hypothesis testing, distributions, and variance analysis, to derive insights.
  • Design and execute model validation frameworks, including cross-validation, A/B testing, and performance tuning.
  • Conduct hyperparameter tuning to improve model accuracy and efficiency.
  • Write optimized and scalable SQL queries for data extraction, transformation, and analysis.
  • Build reusable and scalable Python-based data science pipelines.
  • Collaborate with data engineers and business stakeholders to translate requirements into analytical solutions.
  • Monitor model performance and ensure documentation and reproducibility.
  • Communicate findings, insights, and model outcomes to technical and non-technical stakeholders.
  • Act as a subject matter expert and manage the team to perform; take responsibility for team decisions.
  • Engage with multiple teams and contribute to key decisions; provide solutions for the immediate team and across teams.
  • Lead the design and implementation of AI-driven solutions aligned with business objectives.
  • Facilitate knowledge sharing and mentoring within the team.
  • Coordinate with stakeholders to gather requirements and translate them into technical specifications.
  • Monitor project progress and implement workflow and deliverable improvements.

Desired Qualifications

  • Exposure to healthcare analytics, including claims data, CMS reimbursement, population health, and Medicare Advantage.
  • Familiarity with machine learning lifecycle tools such as MLflow and Azure ML.
  • Exposure to cloud platforms such as Azure, AWS, or GCP.
  • The role is not focused on GenAI or NLP; candidates with heavily LLM-focused profiles without strong core Data Science fundamentals may not be suitable.

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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