Products & Tech - Data Science Senior Associate
Nov 16, 2023
Mexico - Mariano Escobedo 573
Line of Service
Internal Firm Services
IFS - Internal Firm Services - Other
Job Description & Summary
A career in Products and Technology is an opportunity to bring PwC's strategy to life by driving products and technology into everything we deliver. Our clients expect us to bring the right people and the right technology to solve their biggest problems; Products and Technology is here to help PwC meet that challenge and accelerate the growth of our business. We have skilled technologists, data scientists, product managers and business strategists who are using technology to accelerate change.
Our team designs, develops and programs the methods, processes, and systems that are used to collect all forms of data and develop models that serve predictions to applications, automated process flows, and stakeholders. A Data Scientist collects domain context from stakeholders, defines hypothesis and prediction tasks, identifies and creates supporting data sources, conducts experiments with various algorithms to model prediction tasks, undertakes validation and tests of models to improve performance, produces pipelines that can be used to automate training and predictions with unseen or production data, identifies meaningful insights from data sources, and contextualizes model outputs to communicate with stakeholders (product owners, process managers, and end consumers).
To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future.
As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to:
- Use feedback and reflection to develop self awareness, personal strengths and address development areas.
- Delegate to others to provide stretch opportunities, coaching them to deliver results.
- Demonstrate critical thinking and the ability to bring order to unstructured problems.
- Use a broad range of tools and techniques to extract insights from current industry or sector trends.
- Review your work and that of others for quality, accuracy and relevance.
- Know how and when to use tools available for a given situation and can explain the reasons for this choice.
- Seek and embrace opportunities which give exposure to different situations, environments and perspectives.
- Use straightforward communication, in a structured way, when influencing and connecting with others.
- Able to read situations and modify behavior to build quality relationships.
- Uphold the firm's code of ethics and business conduct.
+2 years of experience demonstrating thorough abilities and/or a proven record of success as a team leader in the following areas:
Evaluating new technologies to quickly determine their long term viability within PwCs enterprise wide technology stack, serving 50k+ professionals;
Understanding a business problem and being able to translate the problem into a hypothesis that can be tested using various data science techniques;
Conducting research in a lab environment and publishing work through AI institutes and journals;
Demonstrating thorough understanding of complex machine learning algorithms, data analysis techniques, and data science tools, to address a variety of challenging business problems in the areas of natural language understanding, computer vision, and unsupervised learning;
Building a variety of machine learning models and more importantly, knowing when and why it is appropriate to use each technique: KNN, Logistic Regression, Naive Bayes, Random Forests, Support Vector Machines, XGBoost, Deep Neural Networks, K-means and Hierarchical Clustering, prompt and engineering tuning for LLMs, fine-tuning and domain training LLMs, etc.;
Building machine learning models, data pipelines, and autonomous systems, interpreting their output, and communicating the results to a non technical audience; and,
Performing DevOps/engineering tasks in publishing and deploying AI assets in live production environments suitable for large scale adoption for 55k+ professionals throughout the US.
Demonstrates thorough abilities and/or a proven record of success with a subset of the following technologies:
Large Language model frameworks/libraries including ReAct, Langchain, AutoGPT, Agent GPT, Llama Index, etc.;
Data Storage Technologies including SQL, NoSQL, Hadoop, cloud-based databases such as GCP BigQuery, and different storage formats (e.g. Parquet, etc.);
Data Processing Tools including Python (Numpy, Pandas, etc.), Spark, and cloud-based solutions such as GCP DataFlow;
Machine Learning Libraries including Python (scikit-learn, gensim, etc.), TensorFlow, Keras, PyTorch, and Spark MLlib;
NLP and text extraction techniques including document topic analysis, document clustering and classification, named entity extraction/resolution, creating word/sentence embeddings (numerical vector representations), sentiment analysis etc.;
Code management, model productionization and containerization technologies including GitHub, Flask, Docker, and Kubernetes.
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)
Natural Language Processing (NLP), Natural Language Programming (NLP)
Desired Languages (If blank, desired languages not specified)
Up to 20%
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date