PwC Data Science & Machine Learning SA w/ Conversational AI in New York, New York
Specialty/Competency: Data, Analytics & AI
Industry/Sector: Not Applicable
Time Type: Full time
Travel Requirements: Up to 20%
A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
As part of our Analytics and Insights Consumption team, you’ll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes. You'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights.
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.
Basic Qualifications :
Minimum Degree Required :
Minimum Years of Experience :
Preferred Knowledge/Skills :
Demonstrates thorough abilities and/or a proven record of success in the following areas:
Using analytical models and algorithms including Machine/Deep learning, Multivariate Statistics (e.g., Clustering, Principal Component Analysis, Regression, Hypothesis testing and Factor Analysis), Optimization, and Data Mining, Exploration, and Manipulation;
Leveraging structured and unstructured data for solving analytical problems;
Developing and deploying analytical solutions as part of a larger automation pipeline;
Using common cloud platforms e.g., Azure, AWS and GCP, for manipulating large data sources, model, development, and deployment;
Performing data engineering and cleansing, train-test-validation of models, field testing (A/B Testing), and experimental test & design;
Demonstrating thorough aptitude for conducting quantitative and qualitative analysis;
Converting client problems/requests into appropriate analytical techniques; and,
Explaining analytical/quantitative outcomes to internal and client teams, and correlate it to business value realized;
Demonstrates thorough abilities and/or a proven record of success learning and performing in functional and technical capacities, including the following areas:
Using SQL, Python (e.g. Scikit-Learn, Pandas, SciPy etc.), Relational storage (SQL);
Understanding and/or hands on experience with Alteryx, R, Non-relational storage (NoSQL), tools for data visualization (Tableau, Power BI, etc);
Understanding of conversational (Chats, emails and Calls) data, and the use of this data to train NLP Pipeline and chatbots;
Implementing NLP /NLG techniques such as parts of speech tagging, lemmatization, canonicalization, Word2vec etc.; and,
Implementing bot framework like RASA and NLP tools like LUIS/ Dialog flow or Lex.
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: https://pwc.to/coloradoadvisoryseniorassociate.