# Data Scientist Job Opening at CryptoMize Data Scientist jobs in Delhi at CryptoMize are open on a rolling, always-hiring basis — we staff modeling capacity ahead of the engagements that demand it, not after. This is a full-time, permanent position with immediate joining at our New Delhi HQ, inside the forecasting core whose models have tracked real electoral and reputation outcomes at 89% historical accuracy across 18 countries. The complete job description follows: the responsibilities you will own, the requirements, the seniority path, and the selection process. Practicing data scientists who are tired of models that die in dashboards — and want theirs to face reality — should read to the end. ## Facts - Location: New Delhi (HQ), CDR Building, Chhatarpur - Type: full-time permanent - Availability: immediate, rolling intake (always hiring) - Compensation: discussed at screening ## What you will actually do - Own the modeling layer of live engagements end-to-end — problem framing with the strategist, model design, validation, and the sign-off on what the number actually means - Run forecasting at consequence: electoral trajectory, sentiment inflection, and risk-signal models whose outputs reach client counsel directly - Design segmentation and targeting models for perception and political engagements — the unsupervised work our platforms consume at scale - Build the experimental and quasi-experimental measurement behind reputation interventions, separating real movement from noise with statistical honesty - Set reproducibility standards for the cell — versioned models, pinned data, method notes a peer can reconstruct line by line - Mentor Data Scientist interns and analysts; the teaching culture is why the cell compounds - Carry the miss reviews: every forecast that missed gets a documented post-mortem, and the discipline behind our 89% record is that we study failures more closely than wins ## Skills - Production-grade Python — pandas, scikit-learn, statsmodels pipelines others can run - Statistical rigor — hypothesis testing, regression, Bayesian basics, and validation strategy that survives adversarial data - Machine learning in depth — gradient boosting, clustering, classification, and knowing which model a problem deserves - Time-series forecasting — trend/seasonality decomposition, horizon honesty, backtesting discipline - Experimental design — A/B and quasi-experimental frameworks in messy field conditions - Feature engineering against dirty, manipulated, real-world corpora - Advanced SQL on multi-GB engagement warehouses - Model communication — explaining uncertainty to a strategist who must act on it - Reproducibility engineering — seeds, versions, and audit trails - Mentorship of interns and junior analysts - Discretion with NDA-grade client datasets (non-negotiable) - Domain fluency across politics, reputation, security, and finance — the subject changes weekly ## Tools - Python 3.11 (scikit-learn, statsmodels, XGBoost-class boosters) - Prophet and classical time-series toolchains - PostgreSQL 15 - Git-based model repos with review discipline - Jupyter → production handoff standards ## Questions and answers ### What are the requirements for Data Scientist jobs at CryptoMize? Demonstrated production Python and statistics depth, real ML validation discipline, and at least one body of modeling work you can defend method by method. Formal qualifications are secondary to evidence — we hire on what you can show (clinical-licensed roles are the only exception to this principle). ### Are the Data Scientist job openings in Delhi? Yes — full-time at our New Delhi HQ in Vasant Vihar, working directly with the forecasting core and the strategists its models serve. ### Is this Data Scientist vacancy immediate joining? Yes. Openings are rolling and always active — capacity is staffed ahead of engagements, so strong candidates onboard as soon as notice periods allow. ### What is the salary for a Data Scientist at CryptoMize? Compensation is discussed at screening and depends on demonstrated skill, engagement classification, urgency, and track record. We do not publish figures — each offer is built individually after meeting you. ### What does a Data Scientist do at CryptoMize exactly? They frame engagement problems into modeling problems, build and validate forecasting, segmentation, and experimental-measurement models on real corpora, document the method behind every number, and carry the miss reviews that keep the forecasting record honest. ### What is the career growth for a Data Scientist here? The path runs Data Scientist → Senior → Principal/Forecasting Lead, with a crossover track into Intelligence Strategist for scientists who grow into client counsel. Apply: https://cryptomize.com/careers/job-openings/apply/