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Associate Data Science & Engineering - Data & Analytics (Advisory)

PwC

  • Kolkata, West Bengal
  • 6-8 LPA
  • 2 Years
  • Posted Today
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About the role

PwC (PricewaterhouseCoopers) is one of the world’s leading professional services networks, offering audit, tax, consulting and advisory services across more than 150 countries. In India, PwC has a strong presence with offices in major metros, delivering cutting‑edge solutions to Fortune 500 companies, government bodies and fast‑growing startups. The firm is known for its commitment to building trust, fostering inclusive cultures and driving digital transformation through data‑centric strategies.

As a fresher‑friendly employer, PwC invests heavily in learning platforms, mentorship programmes and global mobility, enabling early‑career talent to grow into future leaders.

The role of Associate – Data Science & Engineering – Data & Analytics (Advisory) in the Kolkata office is positioned within PwC’s Advisory line of service. You will be part of a high‑performing analytics team that helps clients turn raw data into actionable insights. The team works on end‑to‑end data pipelines, builds predictive models, and designs AI‑driven solutions that improve operational efficiency and strategic decision‑making.

As an associate, you will get exposure to real‑world business problems across sectors such as banking, manufacturing, retail and public services, while leveraging the latest cloud and generative AI technologies.

Key Responsibilities

  • Design, develop and validate machine‑learning and deep‑learning algorithms using Python, R and statistical libraries.
  • Build scalable data pipelines on AWS (S3, Glue, Lambda, Redshift, EMR) to ingest, transform and store large‑volume datasets.
  • Implement generative AI solutions (OpenAI, Google Gemini) and integrate them into client‑facing applications.
  • Conduct exploratory data analysis, feature engineering and model performance monitoring.
  • Collaborate with business analysts to translate client requirements into technical specifications.
  • Prepare visual dashboards and data‑storytelling artefacts using tools like Power BI or Tableau.
  • Ensure data quality, governance and security compliance throughout the analytics lifecycle.
  • Participate in code reviews, documentation and knowledge‑sharing sessions within the team.
  • Stay updated with emerging AI/ML trends and propose innovative use‑cases for clients.
  • Support senior consultants in client presentations and proposal development.

Tech Stack: Python, R, SQL, AWS services (S3, Glue, Lambda, Redshift, SageMaker), Spark, Docker, Git, OpenAI API, Google Gemini, Power BI/Tableau, Linux.

Growth Path: Starting as an Associate, high performers can progress to Senior Associate, Manager, Senior Manager and eventually to Director/Partner roles within the Advisory practice. PwC provides structured learning pathways, certifications (AWS, Azure, Google Cloud, TensorFlow) and rotational opportunities across industry verticals.

Why Join PwC: You will work alongside seasoned data scientists and consultants on projects that have tangible business impact. The firm’s emphasis on continuous learning, inclusive culture and global network ensures you gain both technical depth and consulting acumen. Competitive compensation, performance‑linked bonuses, flexible work arrangements and robust employee wellbeing programmes make PwC an attractive launchpad for a data‑analytics career.

Eligibility & process

Who can apply

Graduates with BE/B.Tech/M.Tech in Computer Science, Information Technology, Electronics, Electrical, or related engineering disciplines. Minimum 60% aggregate (or CGPA 6.5/10). No active backlogs at the time of joining. Freshers and candidates with up to 2 years of relevant experience are eligible. Must be able to work from Kolkata office.

Skills & stack

Python AWS Data Engineering SQL Machine Learning Deep Learning Generative AI Data Pipelines

Selection process

  1. Round 1: Online aptitude & logical reasoning test
  2. Round 2: Technical interview focusing on Python, ML concepts and AWS fundamentals
  3. Round 3: HR interview assessing cultural fit, communication and career aspirations

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (Python, AWS, Data Engineering, SQL, Machine Learning, Deep Learning, Generative AI, Data Pipelines) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion PwC Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join PwC as a Associate Data Science & Engineering - Data & Analytics (Advisory)?
Highlight PwC's market reputation, recent tech innovations, and how your skills in Python directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
PwC 6-8 LPA
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