Analytics Lead (Data & Analytics)

Summit Consulting Services; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Summit Consulting Services seeks a hands-on analytics leader to shape and scale our data function across Product and Engineering. You will drive data-driven decision-making, build trusted analytics maturity, and prototype AI-augmented solutions to unlock product value.

In this role you will own data exploration, define metrics, and mentor a growing team while collaborating with senior stakeholders to guide strategic direction. Experience with SaaS data and large-scale datasets is essential.

Qualifications

• Significant experience leading analytics initiatives and shaping data strategy.
• Proven ability to partner with Product and Engineering to drive data-informed decisions.
• Strong communication skills across technical and non-technical stakeholders.

Responsibilities

• Establish the Analytics Function with a clear vision and operating model.
• Partner with Product and Engineering to support roadmap decisions with data.
• Draft robust, analysis-ready datasets from multiple data sources.
• Identify high-impact opportunities where data improves product outcomes.
• Apply AI/ML techniques to improve product functionality and internal workflows.

Skills

Leadership

Analytics strategy

Communication

Mentoring

Education

Bachelor's degree in CS/Engineering/related field

Tools

dbt

Python

SQL

Spark

Job description

This role is focused on enabling better decision-making across the organization through high-quality analysis and the thoughtful application of AI and advanced analytics. You will work closely with Product and Engineering to improve how we understand platform usage, performance, and outcomes, and to shape product direction through data.

This is a hands‑on leadership role. You will define how analytics operates identify high-impact opportunities and deliver meaningful analysisyourself. You will also play a key role in identifying and applying AI capabilities, particularly where they can unlock new product value or significantly improve internal decision‑making.

Given the natureof data products, experience working with financialor market data is highly advantageous.

Key Responsibilities

Establish the Analytics Function

• Define a vision, scope,and operating model for internalanalytics in collaboration with the VP Data and Analytics.
• Identify high-impact opportunities wherebetter data and analysis can materially improvebusiness and product outcomes.
• Establish best practicesfor analysis, experimentation, metric definition, and insight communication.
• Build trust in analytics through rigor, clarity,and transparency.

Product & Engineering Partnership

• Partner closely with Product Managersand Engineering Leads to supportroadmap decisions with data.
• Support the definition and refinement of product metrics,KPIs, and successcriteria.
• Translate ambiguous productand system questionsinto structured analytical approaches.
• Support experimentation and hypothesis-driven product development.

Data Exploration & Analysis

• Work across multiple systemsand data sources(including SaaS platforms, APIs, and operational databases) to discover and extract relevant data.
• Write queries and scripts to retrieve, combine,and prepare data for analysis.
• Build robust, analysis-ready datasets across structured and semi-structured data.
• Identify gaps in instrumentation, tracking, and data availability, and work with engineering to address them.

AI & Advanced AnalyticsApplication

• Identify opportunities to apply AI and machine learningtechniques to improveproduct functionality, internal workflows, and decision‑making.
• Prototype and evaluate AI-drivensolutions (e.g. LLM-powered analysis, classification, summarisation, anomaly detection).
• Work with Engineering to integrate AI capabilities into products or internal tools where appropriate.
• Stay current with emergingAI capabilities and assess theirpractical application withincompany Data and Analytics domain.

Insight Generation & Decision Support

• Conduct exploratory and deep-dive analysisto uncover trends,risks, and opportunities.
• Apply appropriate statistical methods to ensurerobust and reliableconclusions.
• Translate analysis into clear,actionable recommendations for both technical and non-technical stakeholders.
• Develop dashboards or lightweight reporting where appropriate, with a focuson meaningful and decision-relevant metrics.

Grow & Scale the Capability

• Expand analytics supportbeyond Product & Engineering over time.
• Coach and mentor team members,helping to raise the overallanalytical capability of the organisation.
• Define future hiring needs and contribute to building a scalable analyticsand AI function.
• Significant experience in productanalytics, decision science,or data sciencewithin a SaaS or technology environment.
• Proven experience partnering closely with Productand Engineering teams.
• Strong SQL skillsand experience workingwith large-scale datasets.
• Experience writing scripts(e.g. Python, Spark or similar)to retrieve, combine,and analyse data.
• Strong statistical reasoning and ability to apply appropriate analytical methods.
• Experience applying AI/ML techniques to real-world businessor product problems(e.g. predictive modelling, NLP, or LLM-based applications).
• Familiarity with modernAI tooling and frameworks (e.g.Python ML stack,LLM APIs, or similar).
• Ability to rapidly prototype and evaluate AI-driven approaches, and communicate their value and limitations to stakeholders.
• Demonstrated ability to translate ambiguous business problems into structured, data-driven analysis.
• Excellent communication skills,with a focus on influencing decisions and drivingaction.
• Comfortable operating independently and setting directionin an emerging or evolvingfunction.
• Experience in financial services, particularly workingwith trading, securities, market, or regulatory data.
• Experience establishing or scaling an internal analytics or decision sciencefunction.
• Familiarity with modernanalytics tooling (e.g. dbt, BI tools, experimentation platforms).
• Exposure to data governance and metric definition frameworks.

What We Offer

• The opportunity to build and shape the internal analytics capability from the groundup.
• The potential to influence cross-functional decisions throughinsight.
• Close collaboration with senior stakeholders across the organisation.
• A rapidly growingplatform with significant analytical depth and opportunity.