Lead Data Scientist

About Firstsource

Firstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes.

Job Title:

Mode of work

Responsibilities

• Design and implement data-driven solutions to optimize customer experience metrics, reduce churn, and enhance customer satisfaction using statistical analysis, machine learning, and predictive modeling.
• Collaborate with CX teams, contact center operations, customer success, and product teams to gather requirements, understand customer journey objectives, and translate them into actionable analytical solutions.
• Perform exploratory data analysis (EDA) on customer interaction data, contact center metrics, survey responses, and behavioral data to identify pain points and opportunities for CX improvement.
• Build, validate, and deploy machine learning models for customer sentiment analysis, churn prediction, next-best-action recommendations, contact center forecasting, and customer lifetime value optimization.
• Develop CX dashboards and reports using BI tools to track key metrics like NPS, CSAT, FCR, AHT, and customer journey analytics to support strategic decision-making.
• Optimize model performance for real-time customer experience applications through hyperparameter tuning, A/B testing, and continuous performance monitoring.
• Contribute to customer data architecture and pipeline development to ensure scalable and reliable customer data flows across touchpoints (voice, chat, email, social, web).
• Document CX analytics methodologies, customer segmentation strategies, and model outcomes to ensure reproducibility and enable knowledge sharing across CX transformation initiatives.
• Mentor junior data scientists and analysts on CX-specific use cases, and participate in code reviews to maintain high-quality standards for customer-facing analytics.

Skill Requirements

• Proven experience (at least 6+ years) in data science, analytics, and statistical modeling with specific focus on customer experience, contact center analytics, or customer behavior analysis, including strong understanding of CX metrics, customer journey mapping, and voice-of-customer analytics.
• Proficiency in Python and/or R for customer data analysis, sentiment analysis, and CX modeling applications.
• Experience with data analytics libraries such as pandas, NumPy, scikit-learn, and visualization tools like matplotlib, seaborn, or Plotly for customer insights and CX reporting.
• Experience with machine learning frameworks such as Scikit-learn, XGBoost, LightGBM, and familiarity with deep learning libraries (TensorFlow, PyTorch) for NLP applications in customer feedback analysis and chatbot optimization.
• Solid understanding of SQL and experience working with customer databases, contact center data warehouses, and CRM systems (e.g., PostgreSQL, MySQL, SQL Server, Salesforce, ServiceNow).
• Familiarity with data engineering tools and frameworks (e.g., Apache Airflow, dbt, Spark, or similar) for building and orchestrating customer data ETL pipelines and real-time streaming analytics. (Good to have)
• Knowledge of data governance, data quality frameworks, and data lake architectures. (good to have)
• Exposure to business intelligence (BI) tools such as Power BI, Tableau, or Looker for CX dashboarding, customer journey visualization, and executive reporting on customer experience metrics.
• Working knowledge of version control systems (e.g., Git) and collaborative development workflows for customer analytics projects.
• Strong problem-solving skills with customer-centric analytical thinking, and the ability to work independently and as part of cross-functional CX transformation teams.
• Excellent communication and presentation skills, with the ability to explain complex customer analytics concepts to non-technical stakeholders including CX executives, contact center managers, and customer success teams.

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