Website:
revenueoptics.com
Job details:
Data Scientist | Commercial Analytics & Predictive Modeling
Revenue Optics | Full-time | Remote from India | US-aligned hours
Build models that turn customer data into commercial growth.
Revenue Optics is looking for a Data Scientist who can turn messy business data into clear decisions: which customers need attention, what they are likely to buy next, where revenue is leaking, and which opportunities could improve gross profit. This is a career opportunity for someone who can demonstrate strong Python and SQL skills, explain models they personally built, and connect analytical results to business decisions.
ABOUT REVENUE OPTICS
Revenue Optics is a US-based commercial growth company serving B2B distributors, industrial manufacturers and private equity-backed businesses. We help clients strengthen proactive inside sales, improve pricing and profitability, recruit commercial talent, and embed data and AI into everyday commercial workflows. Our clients sell through branches, field sellers, inside sales teams, customer service and distributor channels. Your work will help these teams identify overlooked customers, prioritize opportunities and take relevant sales actions.
Learn more: www.revenueoptics.com
WHAT YOU WILL DO
• Clean, join and validate transaction data, customer and product records, branch structures, sales assignments, pricing data and ERP extracts.
• Identify declining, inactive and at-risk customers. Separate genuine commercial changes from seasonality, stockouts, returns and data quality issues.
• Build customer segments, retention and purchase propensity models, cross-sell recommendations, and reorder or lapsed-product analyses.
• Prioritize opportunities using expected gross profit, confidence and seller capacity.
• Work with pricing specialists to analyze price realization, discount patterns and customer or product margin differences.
• Evaluate models against simple baselines and appropriate holdout data. Explain assumptions, limitations and results.
• Turn findings into usable account lists, dashboards and recommendations that commercial teams can act on.
• Document reusable code and analytical methods so future client engagements require less effort while maintaining quality.
REQUIRED QUALIFICATIONS — PLEASE READ BEFORE APPLYING
• Strong hands-on Python and SQL skills. You must be able to explain and modify your own work.
• At least two substantive analytical projects you personally built, using customer, transaction, product, sales or comparable business data.
• At least one project involving predictive modeling, forecasting or a recommendation system.
• Ability to explain the business problem, dataset, cleaning decisions, method, baseline, validation approach and results.
• Practical understanding of model evaluation, data leakage and appropriate training and testing splits.
• Clear spoken and written English, including the ability to explain findings to nontechnical colleagues.
• Reliable availability for agreed US-aligned working hours.
• Willingness to complete the recorded project walkthrough described below if shortlisted.
This role will typically suit candidates with 1–3 years of relevant experience, but demonstrated ability matters more than tenure. Strong internship, academic and independent projects are welcome when they go beyond reproducing tutorials.
Coursework, certifications, dashboards or AI-generated notebooks alone do not satisfy the modeling requirement.
HELPFUL ADDITIONAL EXPERIENCE
• Customer retention, churn, cross-sell, next-best-product, demand forecasting or pricing analytics.
• ERP, CRM or large transactional datasets.
• Git, reproducible data pipelines, dashboards, deployment or model monitoring.
• B2B distribution, manufacturing or commercial analytics.
You do not need to arrive as an industrial distribution expert. We will teach the operating context. You should be curious about how customers, branches, suppliers, field sellers, inside sales, pricing and gross profit fit together.
REQUIRED VIDEO EXERCISE FOR SHORTLISTED CANDIDATES
If your application matches the role, we will ask you to submit a 5 minute narrated video using Loom, a Teams or Zoom recording, or another recording tool.
Before recording, research Revenue Optics at www.revenueoptics.com.
Your recording should cover:
• Why you fit: Explain how your experience connects to our work in customer growth, sales coverage, pricing or AI-enabled commercial workflows.
• Your strongest modeling accomplishment: Walk through a predictive, forecasting or recommendation project you personally built. Explain the data, your contribution, method, baseline, validation and results.
• A second accomplishment: Briefly describe another relevant project and what your work enabled.
• Business relevance: Explain how you would apply your experience to help a distributor identify declining customers, prioritize opportunities or improve gross profit.
Include specific numbers where available. Clearly distinguish model performance, estimated opportunity and realized business impact. If a project was not deployed, say so.
Simple screen sharing with your own narration is sufficient. Camera-on is optional, and production quality is not assessed. Share only work you are permitted to disclose; sanitized examples are welcome. An equivalent accessible format can be arranged if needed.
You must confirm your willingness to complete this exercise in the application screening. The recording will be requested only after an initial fit review.
WORKING HOURS
This role requires regular alignment with our US team and clients.
Please specify your availability within 5:30 p.m.–2:30 a.m. IST. The window ends the following calendar day. Your exact daily schedule will be agreed during hiring.
Immediate joiners and candidates with notice periods under 30 days receive priority.
Click on Apply to know more.
