PwC
PwC
PwC is a global professional services network supporting businesses, governments, and institutions with audit and assurance, tax, consulting, deals, forensics, and advisory work. Its teams help organizations address digital transformation, artificial intelligence, sustainability, risk management, and regulatory compliance through industry-focused solutions and managed services across sectors worldwide.

Data Science Manager at PwC, Onsite in India

Lead machine learning and analytics solutions for PwC Acceleration Center India. Oversee client engagements, delivery, and data science teams.

Description

  • Develop and deliver data science solutions.
  • Direct client-focused data science strategy execution.
  • Ensure work aligns with PwC goals and vision.
  • Supervise and mentor team members toward high-quality outcomes.
  • Apply firm methodologies and technology to strengthen client service.
  • Build client relationships and oversee complex engagements.
  • Uphold high standards of integrity and professionalism.
  • Find opportunities to improve processes and encourage innovation.
  • Manage project planning, budgets, delivery, and completion.
  • Resolve issues involving clients, team members, and stakeholders.
  • Coach team members, use their strengths, and oversee performance.
  • Adopt technology and innovation to improve delivery.

Requirements

  • Bachelor’s and master’s degree in computer science, engineering, econometrics, statistics, business analytics, or informatics.
  • At least eight years of professional experience.
  • Strong spoken and written English skills.
  • Experience building and deploying machine learning models in cloud environments.
  • Knowledge of supervised and unsupervised machine learning algorithms.
  • Working knowledge of statistics.
  • Experience conducting data analysis.
  • Experience using machine learning frameworks and tools.
  • Advanced SQL and Python or PySpark programming skills.
  • Proficiency with data visualization tools.
  • Working knowledge of containerization.
  • Experience with model explainability and interpretability techniques.

Benefits

  • Practical, hands-on learning opportunities.
  • Access to modern, advanced tools.
  • Inclusive workplace culture.

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