SCM Senior Specialist

Tredence Inc.; Bengaluru; On-site; INR 167,400 - 279,000; Full time

Job summary

Tredence Inc. seeks a Monetization Analyst in Bengaluru, India. This role focuses on establishing core measurement and modeling foundations within the Pricing team, including elasticity and promotional analysis. Candidates should possess advanced SQL skills, problem-solving abilities, basic modeling capabilities, and proficiency in Python. The position will leverage analytical skills to support monetization efforts, requiring fluent English communication skills. Strong candidates may have additional experience in Tableau or optimization methods.

Qualifications

• Advanced SQL writing skills for production-quality queries.
• Ability to perform structured problem-solving and root-cause analysis.
• Basic modeling/ML skills for monetization analytics.
• Understanding of elasticity concepts for pricing and promotional analysis.
• Skill in advanced experimentation and causal inference in product settings.
• Proficiency in Python for data processing and automation.
• Fluent communication in English for technical and non-technical audiences.

Responsibilities

• Write efficient, production-quality SQL.
• Translate ambiguous questions into measurable metrics.
• Support monetization analytics with ML capability.
• Analyze pricing, fees, and promotional incentives.
• Design and interpret results from advanced tests.
• Use Python for analytics workflows.
• Tailor insights to varied stakeholders.

Skills

SQL (advanced)

Problem solving

Modeling / ML capability

Elasticity concepts

Python

Communication in English

Tools

Tableau

Job description

Overview

Role description: Monetization Analyst. For this role, we are specifically looking for a strong ML/modeling profile, as this person will be a founding member of the Pricing team and will help establish core measurement and modeling foundations (elasticity, substitution/cannibalization, and promo impact).

We’re looking for a hands‑on analytics professional to support the company’s Monetization team in building an elasticity library, standardizing promotion measurement, and quantifying substitution impacts across pricing and promotional levers. The role requires strong problem‑solving, quantitative reasoning, and a blend of business acumen and technical depth.

Responsibilities

• Write efficient, production‑quality SQL (advanced).
• Perform structured problem solving and root‑cause analysis; translate ambiguous questions into measurable metrics and crisp analytical plans.
• Basic modeling / ML capability to support monetization analytics work (baseline predictive/analytical modeling orientation).
• Understand elasticity concepts to support pricing, fees, and promotional incentive analysis.
• Apply advanced experimentation and causal inference in a product setting: design tests (power analysis, primary/secondary metrics), interpret results, for hypotheses, and deep dive into drivers as needed.
• Use Python for data processing, automation, and analytics workflows.
• Communicate clearly in fluent English (written and spoken), tailoring insights to technical and non‑technical stakeholders.

Required / Must‑have

• Write efficient, production‑quality SQL (advanced).
• Perform structured problem solving and root‑cause analysis; translate ambiguous questions into measurable metrics and crisp analytical plans.
• Basic modeling / ML capability to support monetization analytics work (baseline predictive/analytical modeling orientation).
• Understanding of elasticity concepts to support pricing, fees, and promotional incentive analysis.
• Apply advanced experimentation and causal inference in a product setting: design tests (power analysis, primary/secondary metrics), interpret results, for hypotheses, and deep dive into drivers as needed.
• Use Python for data processing, automation, and analytics workflows.
• Communicate clearly in fluent English (written and spoken), tailoring insights to technical and non‑technical stakeholders.

Preferred / Good‑to‑have

• Elasticity modeling: Ability to build and maintain an elasticity library to quantify demand response (and supply response where applicable) to pricing, fees, and promotional incentives.
• Substitution / cannibalization measurement: Ability to quantify and explain substitution and cannibalization effects across products, offers, and promotion types.
• Tableau reporting: Ability to build and own complex, self‑service Tableau dashboards and the supporting data pipelines to enable scalable tracking and decision‑making.
• Optimization methods: Exposure to optimization/solver approaches (e.g., linear programming, constrained optimization) for monetization design.
• LLMs for analytics: Exposure to applying LLMs for analytics acceleration, automation, insight generation, or workflow augmentation.