Data Scientist AI Engineer- Senior Manager
Data Scientist AI Engineer- Senior Manager
Posted on :
18-04-2025
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1 Vacancy
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Job Description
Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data Analytics & AIManagement Level
Senior 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 12 years of hands on experience
Position: Senior Manager
Required Skills: Successful candidates will have demonstrated the following skills and characteristics:
Must Have:
Deep expertise in AI/ML solution design including supervised and unsupervised learning deep learning NLP and optimization.
Strong handson experience with ML/DL frameworks like TensorFlow PyTorch scikitlearn H2O and XGBoost.
Solid programming skills in Python PySpark and SQL with a strong foundation in software engineering principles.
Proven track record of building endtoend AI pipelines including data ingestion model training testing and production deployment.
Experience with MLOps tools such as MLflow Airflow DVC and Kubeflow for model tracking versioning and monitoring.
Understanding of big data technologies like Apache Spark Hive and Delta Lake for scalable model development.
Expertise in AI solution deployment across cloud platforms like GCP AWS and Azure using services like Vertex AI SageMaker and Azure ML.
Experience in REST API development NoSQL database design and RDBMS design and optimizations.
Familiarity with APIbased AI integration and containerization technologies like Docker and Kubernetes.
Proficiency in data storytelling and 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 use of GitHub CI/CD code testing and analysis.
Proficient in using AI/ML frameworks such as TensorFlow PyTorch and SciKitLearn.
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 implementing generative AI LLMs or advanced NLP use cases
Exposure to realtime AI systems edge deployment or federated learning
Strong executive presence and experience communicating with senior leadership or CXOlevel clients
Roles and Responsibilities:
Lead and oversee complex AI/ML programs ensuring alignment with business strategy and delivering measurable outcomes.
Serve as a strategic advisor to clients on AI adoption architecture decisions and responsible AI practices.
Design and review scalable AI architectures ensuring performance security and compliance.
Supervise the development of machine learning pipelines enabling model training retraining monitoring and automation.
Present technical solutions and business value to executive stakeholders through impactful storytelling and data visualization.
Build mentor and lead highperforming teams of data scientists ML engineers and analysts.
Drive innovation and capability development in areas such as generative AI optimization and realtime analytics.
Contribute to business development efforts including proposal creation thought leadership and client engagements.
Partner effectively with crossfunctional teams 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 with experience in working across two hyperscale clouds.
Demonstrate effective communication skills coaching and leading junior engineers with a successful track record of building productiongrade AI products for large organizations.
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 46 moreDesired Languages (If blank desired languages not specified)
Travel Requirements
0Available for Work Visa Sponsorship
NoGovernment Clearance Required
NoJob Posting End Date
Required Experience:
Senior Manager
Employment Type
Full-Time
Key Skills
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