Data Scientist AI Engineer-Manager
Data Scientist AI Engineer-Manager
Posted on :
18-04-2025
Employer Active
1 Vacancy
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Job Description
Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data Analytics & AIManagement Level
ManagerJob Description & Summary
At PwC our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.In data analysis at PwC you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive datadriven decisionmaking. You will leverage skills in data manipulation visualisation and statistical modelling to support clients in solving complex business problems.
Years of Experience: Candidates with 8 years of hands on experience
Position: Manager
Required Skills: Successful candidates will have demonstrated the following skills and characteristics:
Must Have:
Strong expertise in machine learning deep learning and advanced statistical modeling.
Experience delivering AIdriven solutions in areas such as forecasting recommendation systems NLP computer vision and optimization.
Strong programming skills in Python PySpark and SQL with a solid understanding of software engineering practices.
Practical knowledge of the AI model lifecycle from data preparation to deployment and monitoring.
Proficient with ML frameworks like TensorFlow PyTorch scikitlearn XGBoost and H2O.
Handson experience in designing and deploying AI pipelines using ML engineering tools such as MLflow DVC Kubeflow and Airflow.
Experience in REST API development NoSQL database design and RDBMS design and optimizations.
Ability to work with big data platforms and tools like Apache Spark Hive and Delta Lake for scalable model development.
Proficiency in data visualization tools such as Tableau Power BI Looker and Streamlit.
Programming skills in Python and either Scala or R with experience using Flask and FastAPI.
Experience with software engineering practices including the use of GitHub CI/CD code testing and analysis.
Skilled in using Apache Spark including PySpark and Databricks for big data processing.
Strong understanding of foundational data science concepts including statistics linear algebra and machine learning principles.
Knowledgeable in integrating DevOps MLOps and DataOps practices to enhance operational efficiency and model deployment.
Experience with cloud infrastructure services like Azure and GCP.
Proficiency in containerization technologies such as Docker and Kubernetes.
Familiarity with observability and monitoring tools like Prometheus and the ELK stack adhering to SRE principles and techniques.
Cloud or Data Engineering certifications or specialization certifications (e.g. Google Professional Machine Learning Engineer Microsoft Certified: Azure AI Engineer Associate Exam AI102 AWS Certified Machine Learning Specialty (MLSC01 Databricks Certified Machine Learning)
Nice to have:
Experience in deploying models to production using CI/CD pipelines and MLOps practices
Exposure to cloud platforms like Azure AWS or GCP including AI/ML services (e.g. Vertex AI SageMaker Azure ML)
Familiarity with API development for AI applications and containerization tools (Docker Kubernetes)
Strong business acumen and ability to communicate technical solutions to nontechnical stakeholders
Roles and Responsibilities:
Lead and manage AI and data science projects from design to deployment ensuring highquality and scalable delivery.
Translate complex business problems into AIdriven solutions leveraging predictive modeling optimization or generative AI.
Architect and oversee the development of AI pipelines and data workflows incorporating best practices for reproducibility and monitoring.
Guide project teams on data engineering model development validation and operationalization.
Communicate technical solutions effectively to business stakeholders through presentations dashboards and storyboards.
Foster strong client relationships by acting as a strategic advisor and aligning AI solutions with business goals.
Mentor junior team members and build a culture of innovation learning and collaboration.
Drive knowledge sharing intellectual property creation and support presales activities through thought leadership and solution development.
Partner effectively with crossfunctional teams including data scientists data managers analysts and infrastructure engineers to develop operationalize integrate and scale new algorithmic products.
Develop code CI/CD and MLOps pipelines including automated tests and deploy models to cloud compute endpoints.
Manage cloud resources and build accelerators to enable other engineers demonstrating practical experience across modern software and AI engineering stacks.
Work autonomously with a successful track record of building multiple largescale productiongrade AI products for large organizations with experience in two hyperscale clouds and effectively communicate while coaching and leading junior engineers.
Professional and Educational Background:
BE / / MCA / / M.E / /Masters Degree /MBA from reputed institute
Education (if blank degree and/or field of study not specified)
Degrees/Field of Study required:Degrees/Field of Study preferred:Certifications (if blank certifications not specified)
Required Skills
Optional Skills
Accepting Feedback Accepting Feedback Active Listening Algorithm Development Alteryx (Automation Platform) Analytical Thinking Analytic Research Big Data Business Data Analytics Coaching and Feedback Communication Complex Data Analysis Conducting Research Creativity Customer Analysis Customer Needs Analysis Dashboard Creation Data Analysis Data Analysis Software Data Collection DataDriven Insights Data Integration Data Integrity Data Mining Data Modeling 43 moreDesired Languages (If blank desired languages not specified)
Travel Requirements
0Available for Work Visa Sponsorship
NoGovernment Clearance Required
NoJob Posting End Date
Required Experience:
Manager
Employment Type
Full-Time
Key Skills
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