Associate Technical Architect - Data Scientist

Quantiphi; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A leading technology firm in Bengaluru is looking for an Associate Technical Architect - Data Scientist with extensive experience in analytics, specifically in the Life Insurance sector. The ideal candidate will collaborate with cross-functional teams to develop actionable data science initiatives, enhancing customer acquisition and operational efficiency. Strong proficiency in Microsoft Azure and hands-on experience with Databricks are essential. Excellent communication skills and the ability to engage senior leaders are critical. This full-time position offers an exciting opportunity to drive impactful data-driven strategies.

Qualifications

• 5+ years of dedicated analytics experience within the Life Insurance sector.
• Experience engaging senior leaders and cross-functional teams.
• Hands-on proficiency with Databricks for data processing.

Responsibilities

• Translate channel strategies into actionable data science use cases.
• Develop and deploy predictive models to improve acquisition strategies.
• Analyze complex insurance data to identify trends and opportunities.

Skills

Statistical methods

Machine learning models

Data processing with Databricks

Understanding of agency dynamics

Education

5+ years analytics experience in Life Insurance sector

Tools

Microsoft Azure

Azure Data Lake Storage

Azure Synapse Analytics

Azure Machine Learning

Job description

Associate Technical Architect - Data Scientist

We are seeking experienced Azure Data Scientists to lead analytics across our multi‑channel distribution, exclusive and independent agency network, and digital customer experience. These roles bridge strategic business goals and actionable data science initiatives, driving measurable impact on customer acquisition, retention, engagement, and operational efficiency. Successful candidates will partner with senior leaders across distribution, marketing, product, UX, and technology teams to design and implement advanced analytics solutions that optimize performance and create value across the customer and agent journey.

Key Responsibilities

• Translate high‑level channel strategies into actionable data science use cases to optimize acquisition, retention, and efficiency.
• Partner with cross‑functional leaders to define, monitor, and communicate KPIs for each distribution channel (e.g., sales funnel analytics, quote‑to‑policy ratios, CAC/LTV).
• Develop and deploy predictive models (lead scoring, next‑best‑action) to improve acquisition strategies.
• Work across multiple functions and use cases across insurance agency, distribution, digital experience and survey analytics.
• Analyze partner and channel performance to recommend resource allocation adjustments.
• Analyze complex insurance data (claims, policies, customer demographics, external data) to identify trends, patterns, and opportunities for business improvement and strategic decision‑making.
• Research and implement cutting‑edge data science techniques and tools to continuously improve analytical capabilities and explore new business opportunities.
• Design, build, and maintain robust, scalable, and production‑ready data science solutions, ensuring their reliability and performance in live environments.

Qualifications

Industry & Domain Expertise

• 5+ years of dedicated analytics experience within the Life Insurance sector, demonstrating a deep understanding of insurance products, policy lifecycle, claims data, and regulatory considerations.
• Deep understanding of distribution models, agency performance dynamics, or digital product engagement.
• Proven track record in optimizing multi‑channel strategies, agency networks, or digital journeys.

Stakeholder Management

• Experience engaging senior leaders and cross‑functional teams (distribution, marketing, finance, UX, engineering).
• Ability to translate complex analytics into clear, actionable recommendations for non‑technical stakeholders.
• Strong facilitation and presentation skills in customer‑facing or consulting contexts.

Data Science Skills

• Expertise in statistical methods (regression, hypothesis testing, time series analysis, classification, clustering).
• Experience in uplift modeling, lifetime value modeling, personalization algorithms, or recommender systems.
• Strong grasp of causal inference, experimentation design, and dashboard development for self‑service analytics.

Technical & Production Experience

• Proven experience designing, developing, and deploying machine learning models and data products into production systems, with a focus on scalability, monitoring, and maintenance.
• Hands‑on proficiency with Databricks for data processing, model training, and deployment.
• Experience working with cloud platforms, specifically Microsoft Azure, including services relevant to data science such as Azure Data Lake Storage, Azure Synapse Analytics, and Azure Machine Learning.
• Proven ability to connect data insights to business strategies and identify opportunities for growth and optimization.
• Demonstrated success in delivering end‑to‑end data science solutions in a commercial setting.
• Experience leading analytics projects from requirement gathering through deployment and stakeholder adoption.

Nice‑to‑Have Skills

• Familiarity with other Azure data services (e.g., Azure Data Factory, Azure Functions) or Google Vertex AI, BigQuery, Adobe Analytics, or Google Analytics.
• Experience in Generative AI and its application in distribution, agency, or digital experience optimization.
• Knowledge of insurance agent compensation models, training, and retention strategies.
• Experience with web behavioral analytics and deep learning for personalization.

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Information Technology
• Insurance

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