Analyse prédictive Jobs

Operational Intelligence Platform for Foreign Trade "Total visibility. Anticipated decisions. Operation under control." The Problem Foreign trade managers face the daily challenge of tracking dozens of simultaneous processes distributed across different teams and operational areas. Each process has critical deadlines, storage fees, free time windows, demurrage risks, and regulatory requirements that, when not monitored in advance, generate fines, delays, and significant financial losses for the company. The current management model relies heavily on human capacity to review spreadsheets, cross-reference information, and identify problems before they become critical. This process is manual, slow, error-prone, and entirely dependent on the availability and attention of each team me...

My immediate goal is to develop robust predictive models that can meaningfully inform cardiovascular research and clinical decision-making. I have aggregated multiple datasets—ranging from structured EHR extracts to imaging-derived variables and device telemetry—and now need a data scientist who can turn these raw inputs into clinically relevant risk scores and outcome forecasts. Scope of work • Clean, integrate, and document the disparate datasets I will share (CSV, SQL dump, and optional imaging features in HDF5). • Engineer features, test several algorithms (e.g., gradient boosting, random forests, neural nets), and iterate toward an interpretable solution. • Provide model performance metrics—AUROC, calibration plots, and decision-curve analysis&m...

I’m rolling out a market-expansion strategy and need a full predictive-analytics design that turns raw market-trends data into clear, actionable forecasts. The goal is simple: surface which regions, segments, and timing windows will give us the highest return as we scale. Here’s what I’m looking for: • A data-pipeline blueprint that pulls, cleans, and stores external market trends feeds (think industry reports, macro indicators, social-buzz dashboards). • A modeling approach—Python with scikit-learn, TensorFlow, or a comparable framework—that can forecast demand shifts and flag emerging opportunities at least one quarter ahead. • Visual outputs (dashboards or notebooks) that make it easy for non-technical stakeholders to compare expansion ...

I’m looking for an expert who can build a reliable predictive AI model that works with time-series data. I have the raw datasets ready; what I need is the full modeling workflow—from exploratory analysis and feature engineering through training, validation, and clear performance reporting. Key objectives: • Choose the most suitable algorithms (e.g., ARIMA, Prophet, LSTM, or hybrids) and justify the selection. • Handle data preprocessing, missing-value treatment, and scaling so the model remains robust in production. • Deliver reproducible code (Python preferred, using frameworks such as TensorFlow, PyTorch, or scikit-learn) and concise documentation that explains setup, hyperparameters, and retraining steps. • Provide evaluation metrics like MAE, RMSE...

I need a neural network expert to develop a model for food formulation analytics. Requirements: - Analyze food formulations and ingredient substitutions - Predict optimal ingredient mixes - Develop taste and texture profiles - Formulation development Ideal Skills: - Experience in predictive analytics - Strong background in neural networks - Knowledge of food science and formulations - Proficiency in Python, TensorFlow, or similar frameworks I would like to design a neuron network software like a company called Giuseppe. I have all the data to populate the databases. 90% of everything is open source.

I need an end-to-end, self-running engine that continuously finds and nurtures B2B prospects for office-space leasing in Gurgaon, focusing strictly on established companies. The platform has to do more than scrape names—it must predict which firms are most likely to relocate or expand, reach out to them with human-sounding messages, and keep the conversation flowing until my sales team steps in. Core workflow • Data sourcing & enrichment: pull fresh company information from publicly available registries, LinkedIn, news feeds, and any other ethical sources, then append decision-maker contacts automatically. • Predictive analytics: score every prospect on its likelihood to lease new space within the next 3–6 months. • NLP-driven email outreach: craft and...

I'm looking for an experienced machine learning specialist to develop a model predicting the likelihood of recurrence for anterior shoulder dislocation. Data Availability: - Clinical records - Patient demographics Outcomes: - Model should predict likelihood of recurrence Labeled Data: - We have fully labeled data for training Ideal Skills and Experience: - Expertise in predictive modeling - Experience with medical datasets - Proficiency in Python, R, or similar - Strong background in clinical risk prediction models Please share relevant past projects and approaches.