**Line of Service** Advisory **Industry/Sector** Not Applicable **Specialism** Data, Analytics & AI **Management Level** Associate **Job 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 data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more [about us](https://www.pwc.in/about-us.html). At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. Responsibilities: • Develop and implement advanced statistical models and machine learning algorithms including time series forecasting, Bayesian modeling, and neural networks to solve complex business problems and drive data-driven decision making. • Design, build, and deploy scalable machine learning models on cloud platforms (Azure/AWS/GCP) using MLOps practices including Dockerization, CI/CD pipelines, and REST APIs to ensure efficient model lifecycle management. • Process, cleanse, and validate large volumes of structured and unstructured data using programming languages such as Python, R, and SQL, ensuring data integrity and quality for analytical purposes. • Architect and maintain robust data pipelines and processing workflows on big data platforms including Hadoop and Elasticsearch, enabling seamless data flow for machine learning operations. • Collaborate with cross-functional teams to translate complex business requirements into actionable data science solutions, effectively communicating technical findings to both technical and non-technical stakeholders. • Leverage deep learning frameworks including PyTorch, TensorFlow, and Keras to build sophisticated neural network models that address advanced analytical challenges and predictive modeling requirements. • Maintain version control systems and collaborative development environments to ensure codebase integrity, facilitate team collaboration, and implement best practices for reproducible data science workflows. Mandatory skill sets: • · Proficient in programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage. · Proficient in Statistical modelling and Machine techniques such as time series forecasting, Reliability models, Markov Models, Stochastic models, Bayesian Modelling, Classification Models, Cluster Analysis, Neural Network, etc. · Good exposure to deep learning and associated frameworks (PyTorch, TensorFlow, and Keras). · Ability to perform preprocessing of structured and unstructured data: Processing, cleansing, and validating the integrity of data to be used for analysis. · Strong working experience with cloud platforms: build, train, and deploy ML Models on Azure/AWS/GCP. · Good working knowledge in distributed computing environments / big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.). · Hand-on experience in the MLOps (Dockerization, REST APIs and the CI/CD/CT processes). · Adaptation of foundation models/LLMs to address specific business challenges. · Utilizing version control for maintaining codebase integrity and collaboration, fostering a collaborative and error-free development environment. · · Good understanding of business and ability to translate domain problems to data science problem. · Ability to communicate effectively with both technical and non-technical stakeholders. Preferred skill sets: · Data analysis, SQL, MLOPS Years of experience required: 6-8 years Education qualification: B.Tech/MCA/BCA/M.tec **Education** *(if blank, degree and/or field of study not specified)* Degrees/Field of Study required: MBA (Master of Business Administration), Bachelor of Engineering, Bachelor of Technology Degrees/Field of Study preferred: **Certifications** *(if blank, certifications not specified)* **Required Skills** Generative AI, Python (Programming Language) **Optional Skills** Accepting Feedback, Accepting Feedback, Active Listening, Algorithm Development, Alteryx (Automation Platform), Analytic Research, Big Data, Business Data Analytics, Communication, Complex Data Analysis, Conducting Research, Customer Analysis, Customer Needs Analysis, Dashboard Creation, Data Analysis, Data Analysis Software, Data Collection, Data-Driven Insights, Data Integration, Data Integrity, Data Mining, Data Modeling, Data Pipeline, Data Preprocessing, Data Quality {+ 33 more} **Desired Languages** *(If blank, desired languages not specified)* **Travel Requirements** Not Specified **Available for Work Visa Sponsorship?** No **Government Clearance Required?** No **Job Posting End Date** July 21, 2026