IN_Manager_Data Scientist, Machine Learning_Data and Analytics_Advisory_Bangalore

Overview

Line of Service
Advisory

Industry/Sector
Not Applicable

Specialism
Data, Analytics & AI

Management Level
Manager

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.

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).

· Intermediate 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:

Data Scientist, Machine Learning

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:

-Experience: Senior Associate – 4 to 7 years

Education qualification:

B.E, B.Tech, MCA, M.Tech, M.E

- Bachelor's degree in computer science; information technology; engineering; information systems and 8+ years’ experience in software engineering or related area at a technology; retail; or data-driven company.

Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor of Engineering, MBA (Master of Business Administration), Bachelor of Technology

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills
Data Science, Machine Learning (ML)

Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Applied Macroeconomics, Business Case Development, Business Data Analytics, Business Intelligence and Reporting Tools (BIRT), Business Intelligence Development Studio, Coaching and Feedback, Communication, Competitive Advantage, Continuous Process Improvement, Creativity, Data Analysis and Interpretation, Data Architecture, Database Management System (DBMS), Data Collection, Data Pipeline, Data Quality, Data Science, Data Visualization, Embracing Change, Emotional Regulation, Empathy {자세히(29)}

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