--- title: 'Data Scientist II at CommerceIQ' canonical: 'https://feeny.ai/job/data-scientist-ii-commerceiq-bengaluru-w9ws7fwzss5p' type: 'job' last_seen: '2026-09-09' --- # Data Scientist II at CommerceIQ - **Company:** CommerceIQ - **Location:** Bengaluru, India - **Posted:** 2026-07-23 - **Last confirmed live:** 2026-09-09 - **Apply:** https://job-boards.greenhouse.io/commerceiq/jobs/7765824003 ## Job description The Company CommerceIQ is building the AI platform that runs commerce for the world's largest brands. We are not selling AI demos. We are shipping AI agents for content, media, and sales into the workflows of the Fortune 100 every week. 2,200+ Customers 10 of Top 12 CPG Companies 900+ Retailers Connected $200M+ Raised Customers include Coca-Cola, Nestlé, Colgate-Palmolive, Mondelez, Samsung, and Kellogg's. Backed by SoftBank, Insight Partners, and Madrona. Headquartered in Mountain View with teams across the US, India, Canada, and the UK. Pre-IPO. Technical Expertise - Strong background in machine learning, statistical modeling, predictive analytics, and feature engineering, with hands-on experience developing and deploying classical ML models. - Strong proficiency in classical machine learning algorithms including Linear Regression, Logistic Regression, Decision Trees, Random Forest, XGBoost, LightGBM, CatBoost, Support Vector Machines (SVM), Naive Bayes, K-Means, and DBSCAN. - Experience with feature engineering, feature selection, dimensionality reduction, hyperparameter optimization, cross-validation, model calibration, and model evaluation. - Proficiency in Python, Pandas, NumPy, Scikit-learn, with experience using libraries such as XGBoost, LightGBM, CatBoost, and Statsmodels. - Experience working with large datasets and data pipelines, including data preprocessing, data quality checks, transformation, aggregation, and feature generation using tools such as SQL, Spark/PySpark, and cloud data platforms. - Strong understanding of statistical methods and model diagnostics, including hypothesis testing, confidence intervals, correlation analysis, distribution analysis, and statistical significance. - Experience with model deployment, monitoring, retraining, and productionization of classical machine learning models. Applied Problem-Solving - Mandatory skill — Demonstrated experience building and deploying classical machine learning models for real-world business problems such as customer churn, credit risk, fraud detection, demand forecasting, customer segmentation, recommendation systems, pricing, propensity modeling, or sales prediction. - Mandatory skill — Strong ability to design, evaluate, and improve ML models using robust validation strategies, cross-validation, hyperparameter tuning, feature engineering, and model comparison. - Experience selecting appropriate algorithms based on business objectives, data characteristics, interpretability requirements, and model performance. - Strong understanding of model evaluation metrics such as ROC-AUC, PR-AUC, Precision, Recall, F1, Log Loss, RMSE, MAE, MAPE/WMAPE, Gini, KS, R², and other domain-specific metrics. - Experience with model interpretability and explainability, using techniques such as SHAP, Partial Dependence Plots (PDP), feature importance, permutation importance, and coefficient analysis. - Experience identifying and addressing data quality issues, class imbalance, overfitting, multicollinearity, feature leakage, model bias, distribution shift, and model drift. - Experience applying statistical and machine learning techniques to NLP, time-series forecasting, classification, regression, clustering, recommendation, or optimization problems. Leadership & Collaboration - Preferred: Proven ability to mentor junior data scientists or analysts, provide technical guidance, and establish best practices for machine learning development. - Strong cross-functional collaboration skills with product, engineering, business, and analytics stakeholders to translate business problems into measurable ML solutions. - Ability to communicate model assumptions, methodology, results, limitations, and business impact to both technical and non-technical stakeholders. - Ability to translate analytical findings into practical, scalable, and measurable business solutions. Education & Experience - 1+ years of hands-on experience in classical machine learning, data science, predictive modeling, or statistical modeling. - Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, Mathematics, Engineering, or a related field, or equivalent practical experience. - Strong analytical and problem-solving skills with the ability to work with structured and unstructured datasets. - Excellent communication and presentation skills, with the ability to explain complex analytical and statistical concepts clearly. - Strong understanding of machine learning fundamentals, statistics, probability, and optimization. - Continuous learner with awareness of classical machine learning techniques, statistical modeling methodologies, model interpretability, and emerging best practices in applied data science. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other category prohibited by applicable law. ## About CommerceIQ ## Company Overview - **One-liner**: CommerceIQ provides a unified AI platform for retail ecommerce teams to automate and optimize sales, content, and media across thousands of retailers globally. - **Entity Type**: Private (Series D, closed in 2022) - **Headquarters**: Mountain View, California, USA (with additional offices in Bengaluru, India and London, UK) - **Founded**: 2018 - **Founders**: Guru Hariharan (CEO) ## Core Business - **Primary industry**: Retail ecommerce technology / AI-driven commerce automation - **Target customers**: B2B – consumer brands (both SMB and enterprise) selling on Amazon, Walmart, Instacart, and 1,450+ other retail endpoints - **Mission statement**: “We drive profitable ecommerce growth with intelligent automation” [[commerceiq.ai/about-us]](https://www.commerceiq.ai/about-us) ## Products & Services - **AllyAI**: An always-on AI commerce operator that automates pricing adjustments, media spend optimization, and content visibility improvements across retailers. Acts as a “co-pilot” for ecommerce teams. - **Content Agent**: Automates management of thousands of SKUs across hundreds of retailers, ensuring accuracy, compliance, and AEO (Amazon Eligibility Optimization). - **Digital Shelf Analytics**: Tracks digital shelf performance 24/7 across 1,450+ retailers, providing prioritized insights and ready-to-use WBR reports. - **eCommerce Sales Management**: Forecasts sales vs. plan, prioritizes next-best actions, and automates execution to close gaps. - **Retail Media Management**: Optimizes retail media bids and pacing using 50+ shelf-aware signals, driving incremental sales. All products are SaaS-based, delivered via a unified platform. ## Market Standing - **Valuation/Market Cap**: Not disclosed (private company) - **Key Metric**: Total funding raised – Series D in 2022 (amount undisclosed); notable investors include Insight Partners, Madrona Ventures, and Shasta Ventures [[commerceiq.ai/leadership]](https://www.commerceiq.ai/leadership) - **Notable Investors/Partners**: Insight Partners, Madrona Ventures, Shasta Ventures; the platform connects to Amazon, Walmart, Instacart, and 1,450+ other retail endpoints - **Growth Signals**: - 2,200+ brands use the platform - Global network of 900+ retailers - In 2021, CommerceIQ automations drove 250 million actions that contributed to profitable market share gains for customers - Offices in US, India, and UK, with a growing global team ## Competitive Advantages - **Unified platform**: One platform covering content, analytics, sales, and media – eliminating siloed tools and spreadsheets. - **AI-native automation**: AllyAI and other agents continuously monitor and act on pricing, content, and media without manual intervention. - **Shelf-aware signals**: Proprietary intelligence that captures real-time shelf data across 1,450+ retailers, enabling better bid optimization and content decisions. - **Deep retailer integrations**: Direct connections to Amazon, Walmart, Instacart, and many others, built specifically for the algorithmic nature of retail marketplaces. ## Strategic Focus CommerceIQ is doubling down on AI-driven automation to help brands scale profitable growth. The company’s leadership principles emphasize “relentless innovation” and “exception-based automated decision making.” Near-term priorities include expanding platform capabilities (e.g., Director of Engineering – AI, Forward Deployed Engineering) and deepening international reach (85+ countries). The company is investing heavily in product teams (AI, data science) and growth partnerships. ## Why Work Here - **Culture & values**: Emphasis on ownership, hiring and developing the best, and moving quickly. Diversity, equity, and inclusion are core to the company’s identity [[commerceiq.ai/careers]](https://www.commerceiq.ai/careers). - **Work model**: Hybrid and remote options depending on role and location; generous PTO including vacation, holidays, and global recharge days. - **Compensation & perks**: Competitive base pay, equity (stock options for eligible roles), comprehensive health/dental/vision insurance, gym stipends, mental health support, and learning & development opportunities. - **Engineering culture**: Strong focus on internal growth and promotion; many team members expand roles from within. Active engineering hubs in Mountain View, Toronto, Bengaluru, and London. - **Global team**: Cross-regional collaboration across US, UK, and India; inclusive environment that values diverse backgrounds. ## Sources 1. [commerceiq.ai](https://www.commerceiq.ai/) – Main site, product descriptions 2. [commerceiq.ai/careers](https://www.commerceiq.ai/careers) – Culture, perks, DEI, hybrid policy 3. [commerceiq.ai/about-us](https://www.commerceiq.ai/about-us) – Mission, metrics, offices, investors 4. [job-boards.greenhouse.io/commerceiq](https://job-boards.greenhouse.io/commerceiq) – Open roles, locations 5. [commerceiq.ai/leadership](https://www.commerceiq.ai/leadership) – Executive team, board of directors, investors ## Other roles at CommerceIQ - [Technical Lead – IT Systems & Asset Management](https://feeny.ai/job/technical-lead-it-systems-asset-management-commerceiq-bengaluru-08p4x8baq8db) — Bengaluru, India - [Director of Finance](https://feeny.ai/job/director-of-finance-commerceiq-bengaluru-bvst1v213anf) — Bengaluru, India - [Senior Account Executive](https://feeny.ai/job/senior-account-executive-commerceiq-united-states-mt7cn25bzcvc) — United States - [Associate Director, Retail Media (Search)](https://feeny.ai/job/associate-director-retail-media-search-commerceiq-united-states-a6pgzgw0h63t) — United States - [Customer Success Manager, Advertising (Retail Search)](https://feeny.ai/job/customer-success-manager-advertising-retail-search-commerceiq-united-states-sz3gqx0k607t) — United States - [Salesforce and IT Infrastructure Administrator](https://feeny.ai/job/salesforce-and-it-infrastructure-administrator-commerceiq-mexico-7z2m8b7cwfbn) — México, Mexico - [Forward Deployed Engineering Manager](https://feeny.ai/job/forward-deployed-engineering-manager-commerceiq-bengaluru-dp38vvv4pmeq) — Bengaluru, India - [Director of Product Management - AI](https://feeny.ai/job/director-of-product-management-ai-commerceiq-mountain-view-california-ghfvm6h4qmtt) — Mountain View California, United States - [No roles that match our current openings? We still want to hear from you—join the CIQ Talent Community!](https://feeny.ai/job/no-roles-that-match-our-current-openings-we-still-want-to-hear-from-you-join-e3q5zpxws19p) — London England, United Kingdom - [No roles that match our current openings? We still want to hear from you—join the CIQ Talent Community!](https://feeny.ai/job/no-roles-that-match-our-current-openings-we-still-want-to-hear-from-you-join-y9qqh3fb8abt) — Bengaluru, India / Chennai Tamil Nadu, India