Artificial Intelligence Analyst jobs in Delhi at CryptoMize are open on a rolling, always-hiring basis. This is a full-time, permanent position with immediate joining at our New Delhi HQ, applying machine learning to the practice’s live intelligence problems. The corpora here are unlike textbook data: multilingual sentiment streams, electoral histories across 18 countries, media-mention floods and coordinated-behavior traces. Analysts build and run the models that turn those into foresight — feeding a forecasting record the practice stakes its name on. You will own models end-to-end: framing the question, engineering the features, validating honestly, and explaining results to strategists who will act on them. The complete job description — responsibilities, requirements, seniority path and selection process — follows.
LOCATION New Delhi (HQ)
EMPLOYMENT Full-time · Permanent
AVAILABILITY Immediate · Rolling intake
COMPENSATION Discussed at screening
TRACKS ON THIS DESK35
CRAFT SKILLS NAMED11
TOOLS & SYSTEMS4
PATH STAGES4
01
01The actual work
What will you actually do as a Artificial Intelligence Analyst at CryptoMize?
01
Build and run learning models on engagement corpora — sentiment trajectories, movement prediction, anomaly and coordination detection
02
Frame engagement questions as learnable problems: what to predict, from what signal, validated against what ground truth
03
Engineer features from messy multilingual media, social and survey data — the difference between a demo and a decision tool
04
Validate honestly: backtesting, leakage control, and communicating uncertainty instead of hiding it
05
Support the practice’s electoral forecasting work — models whose historical accuracy across countries is the product’s signature
06
Write the model documentation strategists actually read: what it predicts, what it cannot, and how confident to be
07
Partner with platform teams to move validated models into production pipelines
ROLE RESPONSIBILITIES
As an Artificial Intelligence Analyst you will apply engineering and statistical learning to the practice’s persistent problems — augmenting what analysts and strategists can see in corpora no human could read whole. Most work addresses recurring pain: movement detection, coordination discovery, forecast support and capability augmentation across engagements.
You will carry models through their full life: framing with the strategist, data and feature work, training, honest validation, and the explanation that makes output usable in client rooms. Program leadership duties include governance of how models are used and change management when they reshape a team’s workflow.
The standard is production thinking — REST interfaces, cloud environments, and pipelines others can rerun — because a model that lives only in a notebook has not happened yet. Client data confidentiality is absolute.
02
02Capability profile
What skills and tools does a Artificial Intelligence Analyst need?
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Craft skills11 Tools & systems4 Offer standards4
Machine learning fundamentals — regression, classification, ensembles, and when simple beats cleverDeep learning literacy — sequence and transformer architectures applied to text and time-seriesNLP on noisy multilingual corpora (tokenization, embeddings, transfer learning)Feature engineering from media, social and behavioral dataRigorous validation — backtesting design, leakage control, honest baselinesPython for ML: pandas, scikit-learn, PyTorch/TensorFlowSQL on multi-gigabyte engagement datasetsUncertainty communication — confidence, error and limitation explained to non-specialistsExperiment discipline: hypotheses logged, results reproducibleDiscretion with client datasets (NDA-grade)Domain curiosity across political, reputation and security questions
Python 3.11 (pandas, scikit-learn, PyTorch)Jupyter-based analysis repos with Git review disciplinePostgreSQL for feature and training dataExperiment tracking (MLflow-class)
Depth of demonstrated skill in the specific role disciplineClassification and scope of the client engagement the role supportsUrgency and time-sensitivity of active project requirementsTrack record built across CryptoMize engagements
Also known as: ai analyst jobs · machine learning analyst · artificial intelligence analyst openings · ml analyst
03
03Seniority ladder
Artificial Intelligence Analyst — seniority path at CryptoMize
ML careers advance on the quality of decisions the models enable — validated, explained, and trusted by the strategists who act on them.
Artificial Intelligence Analyst
Owns models for one to two engagements — sentiment, prediction and anomaly work with senior review.
1/4
Senior Artificial Intelligence Analyst
Designs modeling architecture for new engagements, leads validation standards, and mentors junior analysts.
2/4
AI Analytics Lead
Runs the modeling cell — staffing, standards, and final accountability for every number the practice forecasts.
3/4
AI Practice Principal
The apex: owns the practice’s AI capability end-to-end — research direction, production systems and the analyst bench.
4/4
04
04The engagement surface
CryptoMize work a Artificial Intelligence Analyst touches
Every role plugs into live engagements across the five Penta-P domains — these are the services your work feeds.
Artificial Intelligence Analyst · Job Opening
This seat plugs into 7 live CryptoMize services across the five Penta-P domains — the work below is where yours lands.
7 SERVICESPENTA-P
Predictive Intelligence
Predictive Intelligence Forecasting
Sentiment Analysis
Big Data Mining
Strategic Intelligence
Trend Analysis
OSINT
WHAT DOES ARTIFICIAL INTELLIGENCE ANALYST COMPENSATION DEPEND ON?
Compensation is discussed during screening — never a fixed public figure, because it varies per person and per engagement. It depends on:
# OFFER CONSTRUCTION FACTOR
01 Depth of demonstrated skill in the specific role discipline
02 Classification and scope of the client engagement the role supports
03 Urgency and time-sensitivity of active project requirements
04 Track record built across CryptoMize engagements
