Prediktív analitika Jobs

I am looking for an experienced data analyst / ServiceNow expert to help transform CMDB data into actionable insights and predictive analytics. The CMDB currently receives data from three sources: • Network devices • Software applications • Servers / hardware assets ⸻ Scope of Work: 1. Data Consolidation & Preparation • Review and consolidate CMDB data • Clean and standardise datasets for analysis • Ensure data is usable for reporting and modelling 2. Predictive Analysis • Build simple predictive models to identify early warning signals such as: • Capacity issues • Performance degradation • Configuration drift 3. Dashboards / Reporting / Alerts • Create easy-to-use outputs for operations teams (e.g., dashboard...

Halo! Saya sedang mencari tutor dari Indonesia yang memahami Process Mining, Bayesian Network, dan Random Forest untuk membimbing pengolahan data tesis saya. Saya memiliki paper referensi yang akan menjadi acuan utama. Peran tutor adalah membaca paper tersebut dan mengarahkan saya langkah demi langkah sesuai framework yang digunakan. Saya akan mengerjakan prosesnya sendiri, kemudian tutor membantu melakukan review dan koreksi jika terdapat kesalahan. Setelah itu, tutor juga membimbing saya dalam implementasi Random Forest hingga tahap olah data selesai. Ruang Lingkup Pekerjaan: - Membaca dan memahami paper referensi yang disediakan. - Mengarahkan langkah-langkah analisis sesuai framework pada paper. - Mereview dan memberikan masukan terhadap hasil olah data yg saya lakukan - Sesi diskusi...

I have a flow of numerical data arriving on a regular basis and I want the entire predictive-analysis cycle handled automatically in Python. The goal is a script or small pipeline that can pull the fresh data, clean and transform it, train or update a predictive model, and then return the forecasts (plus standard performance metrics) without manual intervention. I expect you to choose the appropriate Python libraries—think pandas for wrangling, scikit-learn or a comparable framework for modelling, and perhaps joblib or pickle for model persistence—and stitch them together in a way that lets me trigger everything with a single command or scheduled job. Clear, well-commented code and a short README that shows how to run the automation are part of the deliverable. If you can set ...

? HAGO Contest #2 – April ? For data scientists and analytics enthusiasts, we present a new challenge with Amazon sales dataset. ? Tasks: Explore the dataset in depth Analyze patterns and trends Build a predictive model using Python Submit results in a PDF file within our private community ? Prize: The winner receives $15 USD for the best analysis and prediction ? Don’t forget to join the IFAI Contest for future forecasting, where the winner earns $10 USD. ✨ Tips to increase your chances of winning: Make your analysis comprehensive yet easy to understand Add clear and insightful visualizations Focus on prediction accuracy and creative ideas

"Traders in my System" — Your gateway to institutional-grade capital. I am the founder of Alpha Genesis Advisors, and I am currently recruiting elite traders and community leaders to join our rapidly expanding prop-trading ecosystem. We don’t just follow the market; we dominate it using high-frequency algorithms and predictive analytics. What We Offer: Direct Capital Allocation: I am providing my own private capital for 1-2 initial trading sessions. You don't need to risk your own funds—prove your edge, and we provide the leverage. 40/60 Profit Split: Our model is simple and transparent. You keep 60% of the profits, while 40% is reinvested into the growth of our global fund. This is a partnership built for the long term. Technological Superiority: Our s...

Looking for a highly skilled Data Scientist with deep expertise in AI and Generative AI to lead cutting-edge retail merchandising and pricing analytics initiatives, driving scalable forecasting, optimization, and intelligent automation solutions. -Leverage state-of-the-art AI and Generative AI techniques to drive innovation in retail merchandising and pricing analytics. -Design, develop, and deploy advanced machine learning and optimization models to support data-driven business decisions. -Build scalable solutions for demand forecasting, assortment optimization, price elasticity modeling, and inventory allocation and replenishment. -Develop sophisticated demand forecasting systems using multivariate and hierarchical models for long-range, multi-echelon predictions. -Address complex f...

I need a detailed systematic review on "machine-learning early detection warning system for intraoperative hypotension." This review is for academic submission and should be 23-25 pages in length (double spaced) with no intention to publish. I will provide the reference list (see below towards the bottom). Please expect that I will need revisions of the draft as my school will requires changes as they per their suggestions. PLEASE NOTE: my school is VERY strict with using AI to write the actual paper. It's fine to use AI for support, but not in the actual writing out of the paper. This is why I'm outsourcing this. Key Focus Areas: - Clinical outcomes with an emphasis on accuracy of predictions and reduction in adverse events - Comprehensive analysis of clinical tri...

Quiero poner en línea una página de gemelo digital que ayude a mi flota a adelantarse a las averías. El foco no es la localización ni la planificación de rutas, sino el mantenimiento predictivo: necesito que el sistema analice el historial de mantenimiento combinado con las condiciones operativas actuales y anticipe cuándo cada vehículo requerirá intervención. Los datos que ya tengo disponibles son: • Historial de mantenimiento en hojas de cálculo y vía API. • Condiciones operativas que llegan en tiempo casi real desde nuestro ERP (horas de motor, temperatura de trabajo, kilometraje, etc.). En la interfaz quiero ver todo de forma clara: tablas y gráficas que permitan filtrar por vehícul...

I’m looking for someone who can turn our raw internal database records into forward-looking insights. The data is already well-structured in SQL tables; what I need now is a predictive layer that helps us forecast key metrics and identify the drivers behind them. You’ll have direct read-only access to the relevant tables along with a short data dictionary. From there, please choose the techniques and tools you’re most comfortable with—whether that’s Python (pandas, scikit-learn), R, or another established machine-learning framework—so long as the final model is reproducible and the code is clearly documented. The deliverable I expect is a concise notebook or script that: • cleans and preps the data, • trains and validates at least one...

An "attractive" project is one that balances high-impact results with a clear, aesthetically pleasing presentation. Whether it's for a portfolio, a promotion, or a passion project, the most compelling examples usually follow a specific structure: Problem → Sophisticated Solution → Tangible Results. ​Here is an example of a high-impact project layout in the tech/data space: ​Project Title: "Urban Pulse" – Real-Time Transit Optimization ​1. The Challenge ​Municipal bus routes in mid-sized cities often suffer from "ghosting" or inefficient scheduling because they rely on static historical data rather than real-time demand. This leads to a 15% increase in average commuter wait times during peak hours. ​2. The Solution ​I developed a predictive...

I maintain A320, A321, and A330 fleets every day and know first-hand how much time can be lost hunting through the AMM. I’m now turning that experience into a mobile application whose core job is to walk a mechanic through genuine Airbus maintenance logic, step by step, the moment a fault code appears. The workflow I have in mind is simple for the user yet sophisticated behind the scenes. A technician selects or scans the reported fault; the app immediately serves the relevant AMM decision tree, predicts the likeliest branch using predictive analytics, and records each action the mechanic takes. At the end of every task the app stores the completed log so that subsequent interventions on the same tail number draw on real, aircraft-specific history rather than a blank slate. Data yo...

I'm seeking an expert in AI algorithm design to create a comprehensive bowling assistant. The algorithm should: - Predict ball trajectory - Analyze player performance - Suggest optimal bowling techniques Ideal candidates will have: - Strong background in AI and machine learning - Experience in sports analytics - Proven track record in algorithm design Please include relevant experience in your application. So professionals have ball reps who stand behind them. Suggest ball changes, scout lanes etc. What if we have an AI app that you can input your bowling balls, core, covers. Input your ball speed, axis tilt, pap etc. Input the lane condition bowling on and then input where you are standing what ball your threw and the result. You can say that ball didnt hook when I hit this mark...

This project focuses on applying data analytics techniques to solve a real-world business problem involving marketing performance optimization. The main objective was to determine the most effective advertising platform and predict future conversions using statistical and analytical methods. The project begins with defining a clear business problem, followed by collecting and cleaning campaign performance data. Exploratory Data Analysis (EDA) was conducted to understand patterns, trends, and key variables affecting performance. A/B testing was implemented to statistically compare different advertising platforms and determine which one performs better in terms of engagement and conversions. This helped in making evidence-based decisions rather than relying on assumptions. Further, regres...

I want to spin up a data-analysis bot that can be trained to act as a credit analyst. Its core duties will be credit risk assessment, financial reporting, and running predictive analysis on lending portfolios. I have not yet settled on the underlying LLM—Claude, GPT-4, or possibly a hybrid approach—so part of this engagement is your guidance on the best stack (e.g., LangChain orchestration, vector store, retrieval strategy) for accuracy, cost-efficiency, and explainability. Here is what I need to walk away with: • A working agent hosted in a cloud environment (or locally if more practical) that ingests structured and unstructured financial data, runs the three tasks above, and produces clear, exportable outputs. • A concise technical document covering architectu...