ETIC, Machine Learning, Senior Associate
صاحب العمل نشط
حالة تأهب وظيفة
سيتم تحديثك بأحدث تنبيهات الوظائف عبر البريد الإلكتروني
شارك هذه الوظيفة
حالة تأهب وظيفة
سيتم تحديثك بأحدث تنبيهات الوظائف عبر البريد الإلكتروني
الوصف الوظيفي
Line of Service
AdvisoryIndustry/Sector
TechnologySpecialism
Advisory - OtherManagement Level
Senior AssociateJob Description & Summary
As a Machine Learning Engineer in the FS AI team you will use techniques such as machine learning and natural language processing to realise authentic data-driven change and team reports to the board and commercial executive and works with clients and PwC leadership across our business units to enhance performance and have impact on value creation.Responsibilities
Designing and developing data science and machine learning assets for PwC and its clients
Contributing effective useful code to our Data Science codebase
Participating in constant learning through training and skills development
Deploying and managing machine learning models in production environments ensuring scalability reliability and performance monitoring
Embedding Responsible AI practices across the model lifecycle ensuring fairness transparency explainability bias mitigation and compliance with ethical and regulatory standards
Contributing to the strategy and growth of a fast developing data science capability
Craft and communicate compelling business stories based on analytics insight
Business case and Proposal development
Presenting findings to senior internal and external stakeholders
Being part of this technology innovation effort of the Firm
Key Skills Required
4 Years Experience
Statistical Analysis & Machine Learning Theory Excellent understanding of statistics machine learning techniques and algorithms. Hands-on experience with regression classification clustering and other classical statistical models and algorithms Must have Advanced
Independently formulate hypotheses choose and justify appropriate statistical tests and interpret results
Select implement and tune ML algorithms (e.g. random forests SVMs gradient boosting) end-to-end and explain the mathematical foundations and assumptions behind them
Hands-on experience designing and validating models for regression classification and unsupervised learning tasks
Deep understanding of biasvariance tradeoff regularization techniques and feature selection methods
Machine Learning Lifecycle Management Experience delivering end-to-end solutions from data sourcing and preprocessing through model deployment and results interpretation Must have Advanced
Architect and execute full pipelinesfrom data ingestion and feature engineering through model training validation deployment monitoring and retraining using best practices in reproducibility and CI/CD
Troubleshoot production issues (drift latency scaling) and optimise models for performance and cost
Agile Methodologies Ability to work effectively in an agile delivery environment participating in sprint planning stand-ups and retrospectives Must have Intermediate
Participate effectively in sprint planning daily stand-ups and retrospectives
Break work into user stories estimate tasks and collaborate with product owners to groom the backlog
Requirements Gathering & Translation Skill in partnering with product owners to translate business needs into data science requirements and success metrics Must have Advanced
Lead interactions with stakeholders to outline clear business objectives and translate them into measurable data science success metrics.
Draft technical specifications and align on KPIs risk factors and roadmap milestones
Data Science Project Execution Demonstrable track record of completing data science projects (professional academic or personal) with a clear business focus Must have Advanced
Own multiple data science projects from proof-of-concept through delivery ensuring alignment with business value and timelines
Document methodologies maintain reproducible codebases and present actionable insights to senior leadership
Python Programming Strong programming skills in Python including libraries like pandas NumPy scikit-learn and others for data manipulation and modeling Must have Advanced
Write clean modular well-tested Python code
Build custom utilities or packages optimize critical code paths (vectorization parallelism) and manage dependencies
SQL Querying & Data Manipulation Practical knowledge of SQL for extracting transforming and loading data from relational databases Must have Intermediate
Extract and join complex datasets from relational databases write performant queries (window functions CTEs) and perform ETL tasks
Version Control & Git Proficiency with Git for source code management branching strategies merging and collaborative workflows Must have Intermediate
Use feature branching pull requests and code reviews in a team setting
Data Science Communication Ability to articulate complex data science concepts and results clearly to both technical and non-technical stakeholders Must have Intermediate
Craft clear concise narratives around model design performance and business impact for both technical and non-technical audiences
Design and deliver visuals (e.g. dashboards slide decks annotated charts) that guide stakeholders through your methodology results and recommended actions
Team Collaboration & Knowledge Sharing Enjoy working in cross-functional teams and learning from peers contributing to collective problem-solving Must have Intermediate
Mentor junior engineers and foster a culture of continuous learning
Contribute to peer code reviews internal tech talks or knowledge sharing sessions
Nice to have
Deep Learning Frameworks Proficiency with frameworks such as TensorFlow PyTorch Keras Theano or CNTK for building and training neural networks Intermediate
Cloud Computing Platforms Experience working in cloud environments (Azure GCP or AWS) including managing resources pipelines and scalable deployments Intermediate
Privacy Enhancing Techniques (PETs) Some experience with homomorphic encryption federated learning differential privacy etc. Intermediate
Relevant experience areas
Machine Learning Generative AI MLOps & CI/CD Cloud Native ML Services
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 AI Implementation Analytical Thinking C Programming Language Communication Complex Data Analysis Creativity Data Analysis Data Infrastructure Data Integration Data Modeling Data Pipeline Data Quality Deep Learning Embracing Change Emotional Regulation Empathy GPU Programming Inclusion Intellectual Curiosity Java (Programming Language) Learning Agility Machine Learning 26 moreDesired Languages (If blank desired languages not specified)
Travel Requirements
0%Available for Work Visa Sponsorship
NoGovernment Clearance Required
NoJob Posting End Date
Required Experience:
Senior IC
نوع التوظيف
دوام كامل
