IN_Senior Associate_Data modelling_ Data and Analytics_Advisory_Pan India

Job description

**Line of Service** Advisory **Industry/Sector** Not Applicable **Specialism** Data, Analytics & AI **Management Level** Senior 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 business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision-making for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage. 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. 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**   - Design and implement scalable forecasting and predictive analytics models to solve complex business challenges across multiple domains. - Develop and   optimize   data models (logical, physical, dimensional, and semantic) to support analytics, ML, and reporting use cases. - Work with large, complex datasets from multiple sources—cleansing, transforming, and preparing them for analytical consumption. - Build, train, and evaluate ML models using statistical and machine learning techniques to enhance accuracy, performance, and interpretability. - Collaborate with data engineers and cloud teams to integrate ML pipelines into AWS or Azure environments using modern ETL and orchestration tools. - Translate business   objectives   into technical data solutions and actionable insights through strong analytical reasoning and stakeholder communication. - Ensure data quality, lineage, and consistency through standardized data definitions, metadata documentation, and model versioning practices. - Continuously improve models through retraining, drift detection, and performance monitoring using   MLOps   best practices. - Build SQL queries,   tables   & schemas   for large   datasets   converting unstructured data into meaningful transformations for analysis. - Desing   statistical test s ,   model assumptions ,   build   EDA reports & POCs as and when   required .   Required Skills and Experience  - Proven   expertise   in machine learning and statistical modeling for forecasting, demand prediction, or time-series analysis. - Strong data modeling skills across dimensional, relational, and semantic structures. - Advanced   proficiency   in Python for data wrangling, feature engineering, and ML model development (Pandas, NumPy, Scikit-learn,   PyTorch /TensorFlow preferred). - Strong practical   & theoretical   knowledge of statistical concepts including data science models . - Strong   SQL skills with experience writing efficient queries and   optimizing   database performance. - Strong analytical and problem-solving mindset with the ability to derive insights and communicate outcomes to technical and business stakeholders.   **Mandatory Skill sets:**     Good exposure to retail and consumer  Technical skills  ML engineer with vast experience in solving prediction and forecasting with strong practical knowledge of all traditional machine learning models & deep learning models.  Data Modelling is   a must   (building relational data & table schema)  Strong knowledge of theoretical   & practical   concepts of   statistics   including logical   & statistical   understanding of ML models.  ETL/Data Engineering skills on AWS/Azure   is   good to have.  Advance level SQL skills.  Python skills   excellent.  Knowledge of GenAI & Agentic AI is good to have.  Knowledge of   MLOps   intermediate level.      **Preferred Skill sets:**   - Domain experience in retail, supply chain, demand forecasting, or CPG analytics. - Strong interest in emerging areas such as Generative AI or AI-driven forecasting automation. - Exposure to   cloud ecosystems (AWS, Azure) including data engineering components like Glue, Data Factory, Lambda, Databricks, or Synapse. **Years of experience required:** 4-8 Yrs **Education qualification:** B.E, B.Tech, M.E, MCA, M.Tech **Education** *(if blank, degree and/or field of study not specified)* Degrees/Field of Study required: Bachelor of Technology, MBA (Master of Business Administration) Degrees/Field of Study preferred: **Certifications** *(if blank, certifications not specified)* **Required Skills** Data Science, Machine Learning **Optional Skills** Accepting Feedback, Accepting Feedback, Active Listening, Analytical