Head of Analytics & Data Science
- UK Based Global
- 15 - 24 years
- Noida, Gurugram
- 10 hours ago
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Job Description
- Job Title: Head of Analytics & Data Science BPM(Multi-Vertical)
- Location: India Gurgaon
- Department: Analytics
- Reports to: Chief Capability Leader
Experience Required: 18+ years (with at least 5 years in senior analytics and data science leadership across multiple industries)
Education: Masters or Bachelor's in Data Science, Statistics, Engineering, Business, or related field
Job Summary:
The Head of Analytics & Data Science will lead the end-to-end data and analytics strategy across multiple BPM industry verticals, delivering actionable insights, digital transformation, and measurable business impact to internal stakeholders and global clients. This role demands deep expertise in analytics and advanced data science, combined with strong domain knowledge across Shipping & Logistics, Telecom, Insurance, Energy & Utilities, Retail & Diversified, Banking & Financial Services (BFS), Healthcare & Life Sciences, Automotive, and Travel & Leisure. The ideal candidate will drive analytics and data science maturity, scalable delivery models, and innovation through AI/ML, automation, and applied data intelligence.
Key Responsibilities:
1. Strategic Analytics & Data Science Leadership
- Define and execute a unified analytics and data science roadmap aligned with the organizations digital and business transformation goals across all verticals.
- Champion the integration of advanced data science techniques (predictive modelling, optimization, machine learning) into core business functions.
- Collaborate with business leaders to embed data-driven decision-making into strategic and operational processes.
2. Client-Facing Solutioning & Delivery
- Serve as the senior advisor to clients, leading discovery sessions, solution design, and execution of advanced data science and analytics programs.
- Design customized, vertical-specific analytics and AI/ML solutions:
- Shipping & Logistics: Route optimization, warehouse analytics, predictive delivery
- Telecom: Churn prediction, usage pattern modelling, customer lifetime value
- Insurance: Fraud detection, risk scoring, claims analytics
- Energy & Utilities: Load forecasting, asset health modelling
- Retail & Diversified: Customer 360, pricing optimization, market basket analysis
- BFS: Risk modelling, credit scoring, anti-money laundering (AML) analytics
- Healthcare & Life Sciences: Patient outcome prediction, RWE analytics, care pathway modelling
- Automotive: Predictive maintenance, quality analytics, connected vehicle data modelling
- Travel & Leisure: Dynamic pricing, demand forecasting, personalization and loyalty analytics
3. Operational Analytics & Governance
- Establish and enforce best practices in data science model lifecycle management, data governance, and analytical operations.
- Drive efficiency and SLA improvements through continuous monitoring, dashboards, and KPI frameworks.
- Ensure model explainability, compliance (e.g., GDPR, HIPAA), and responsible AI principles in delivery.
4. Team Development & Leadership
- Build and lead high-performance global teams of data scientists, ML engineers, BI developers, and domain experts.
- Establish Centers of Excellence (CoEs) for analytics and data science by industry vertical and capability.
- Foster a culture of experimentation, innovation, and continuous learning in AI, ML, and data science.
5. Technology & Innovation Enablement
- Oversee the adoption of best-in-class platforms and tools:
- BI: Power BI, Tableau, Qlik
- Data Science & ML: Python, R, SAS, TensorFlow, Scikit-learn
- Cloud & Big Data: AWS, Azure, GCP, Spark, Databricks
- Lead initiatives involving generative AI, NLP, and real-time analytics to improve process automation and customer experience.
6. Data Science Excellence
- Own the design and scaling of ML pipelines, model ops frameworks, and AI-driven workflows across client programs.
- Introduce innovation in forecasting, classification, clustering, and optimization models.
- Build partnerships with academic institutions, AI labs, and vendors to continually enhance the firms data science maturity.
Key Skills & Competencies:
- Deep multi-vertical expertise with strong domain understanding across listed industries
- Expertise in data science, statistical modelling, and ML deployment at scale
- Strong consultative, problem-solving, and solution architecture capabilities
- Executive presence and stakeholder management with global clients
- Proven ability to build analytics and data science teams, COEs, and delivery frameworks
Preferred Background
- Senior leadership experience in analytics and data science within a BPM/KPO/Shared
- Services/Consulting environment
- Track record of driving data science-led transformation in client engagements
- Experience delivering programs for US, UK/EU, and APAC markets
- Familiarity with regulatory requirements and ethical AI standards across industries
Job Classification
Industry: BPM / BPOFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Head - Data ScienceEmployement Type: Full timeContact Details:
Company: UK Based GlobalLocation(s): Noida, Gurugram
Keyskills: Data Science Data Science Excellence data science maturity Data Analytics Statistics applied data intelligence Operational Analytics Advanced Analytics Governance advanced data science Python scalable delivery models
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