Labs - Data Scientist - Senior Associate

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

PwC Labs is focused on standardizing, automating, delivering tools and processes and exploring emerging technologies that drive efficiency and enable our people to reimagine the possible. Process improvement, transformation, effective use of innovative technology and data & analytics, and leveraging alternative delivery solutions are key areas of focus to drive additional value for our firm. The AI Lab focuses on implementing solutions that impact efficiency and effectiveness of our technology functions. Process improvement, transformation, effective use of technology and data & analytics, and leveraging alternative delivery are key areas to drive value and continue to be recognized as the leading professional services firm. AI Lab is focused on identifying and prioritizing emerging technologies to get the most out of our investments.

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.

Job Requirements and Preferences: Basic Qualifications:

Minimum Degree Required: Bachelor Degree

Additional Educational Requirements: In lieu of a Bachelor Degree, 12 years of professional experience involving technology-focused process improvements, transformations, and/or system implementations

Minimum Years of Experience: 2 year(s)

Preferred Qualifications:

Degree Preferred:Master Degree

Preferred Fields of Study: Computer and Information Science, Mathematics, Computer Engineering, Artificial Intelligence and Robotics, Statistics, Data Processing/Analytics/Science

Preferred Knowledge/Skills: Demonstrates 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, 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:

• Programming including Python, R, Java, JavaScript, C++, Unix Hardware, sensors, robotics, GPU enabled machine learning, FPGAs, and Raspberry Pis, 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.;
• Visualization including Python (Matplotlib, Seaborn, Plotly, bokeh, etc.), and JavaScript (d3); and,
• Code management, model productionization and containerization technologies including GitHub, Flask, Docker, and Kubernetes.

At PwC, our work model includes three ways of working: virtual, in-person, and flex (a hybrid of in-person and virtual). Visit the following link to learn more: https://pwc.to/ways-we-work.

PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.

All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law. PwC is proud to be an affirmative action and equal opportunity employer.

For positions based in San Francisco, consideration of qualified candidates with arrest and conviction records will be in a manner consistent with the San Francisco Fair Chance Ordinance.

For positions in Colorado, visit the following link for information related to Colorado's Equal Pay for Equal Work Act: