Data Science Manager

Overview

In this Data Science Manager role, you will lead and inspire a team of data scientists to build bespoke machine learning solutions that address real business needs. You’ll translate client requirements into scalable analytics, guide discovery and opportunity identification, and partner with engineers to deploy models at scale. You’ll influence client direction with data-driven insights and contribute to sales activities, all within Accenture’s Applied Intelligence practice and global Data & AI ecosystem.

Pay / Benefits

• 30 days vacation per year
• gym subsidy
• private medical insurance
• 3 extra days leave per year for charitable work

Responsibilities

• Lead, motivate and inspire teams of Data Scientists
• Create bespoke machine learning solutions to model/solve problems and develop the team
• Solve challenging business problems using advanced machine learning methods (Deep Learning, quantitative analytics)
• Understand business requirements and support the development of business cases
• Run discovery analytics to identify new and innovative opportunities
• Partner with developers and engineers to deploy, embed and scale machine learning models to deliver complex projects
• Devise reusable assets, solutions and best practices for current and future business problems
• Lead analytical discussions and influence analytical direction of client’s teams
• Communicate and provide guidance to senior client leadership and teams
• Contribute data science expertise to new sales activities

Key requirements

• Relevant work experience in data science, machine learning, and business analytics
• Practical experience in coding languages (Python, R, Scala)
• Strong proficiency in database technologies (SQL, ETL, No-SQL, DW) and Big Data technologies (pySpark, Hive)
• Experience with structured and unstructured data (text, PDFs, images, call recordings, video)
• Knowledge of ML modeling techniques and fine-tuning (XGBoost, Deep Neural Networks, Transformers, etc.)
• Experience using ML libraries (Fastai, Keras, TensorFlow, PyTorch, scikit-learn, HuggingFace)
• Ability to read, understand and implement new ML techniques as they emerge
• Experience with Cloud technologies (AWS, GCP or Azure)
• Specialised visualization techniques (D3.js, ggplot)
• Strong verbal/written communication and data presentation skills

• Leadership and people management
• Strong communication and presentation skills
• Cross-functional collaboration
• Python, R, Scala
• SQL, ETL, NoSQL, DW, PySpark, Hive
• ML modeling techniques (XGBoost, transformers, DNNs)

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