Data Science Jobs

## Proyecto: Plataforma de IA para Predicción y Análisis de Apuestas Deportivas (Nivel Avanzado) ### Descripción general Estoy desarrollando una plataforma avanzada de análisis deportivo basada en inteligencia artificial llamada FINAL BOSS QUANT, enfocada en generar predicciones altamente precisas para apuestas deportivas (MLB, NBA, UFC, Soccer, etc.). El sistema combina múltiples modelos matemáticos y estadísticos como: - Modelos de Poisson - Simulación Monte Carlo (gran escala) - Análisis Bayesiano - Machine Learning (Auto-ML) - Value Betting (detección de valor esperado positivo) El objetivo es construir un sistema profesional, modular y altamente optimizado que pueda competir con herramientas de nivel institucion...

I need a compact, easy-to-use application that takes our historical sales data for multiple molecules and converts it into reliable demand forecasts over weekly, monthly, and quarterly horizons. Accuracy and transparency are essential because the results will drive production planning and purchasing decisions across several plants. Core scope • Ingest CSV or Excel files of historical sales pulled from our ERP. • Clean, normalize, and visualize the data so outliers or seasonality jumps are obvious. • Apply proven time-series or machine-learning techniques (ARIMA, Prophet, LSTM—whichever best fits the data volume and variability) to generate baseline forecasts and confidence intervals. • Allow me to tweak parameters—e.g., switch models, adjust seasona...

I’m building a full-featured AI sales assistant that can 1) hold natural, on-brand conversations with prospects and customers, 2) surface real-time sales analytics, and 3) automate lead capture, scoring, and routing—all in one seamless product. Core scope The software must combine an LLM-driven conversation engine with a data layer that feeds dashboards and predictive models. It should talk to every place my team already works, so native, bidirectional integrations are essential with: • CRM systems (Salesforce, HubSpot, Zoho, etc.) • Email platforms (Gmail, Outlook 365, Mailchimp, …) • Social media channels (LinkedIn, Facebook, Twitter/X) Key expectations • Modular, API-first architecture that lets me swap models or data sources without hea...

Project Brief: AI-Based Auto Trading Signal System Goal Build an AI system that automatically generates buy/sell signals for trading instruments (Gold, BTC, and others) and adapts to live market conditions for intraday trading. Core Features Needed 1. Data Ingestion Live price feeds (via APIs like Binance, Yahoo Finance, Alpha Vantage) OHLCV data (Open, High, Low, Close, Volume) News/sentiment feed (optional but powerful) 2. AI Signal Engine ML models (LSTM or XGBoost) trained on historical price data Auto-generates Buy / Sell / Hold signals No hardcoded strategy — model learns patterns from data itself 3. Adaptive Market Condition Detection Automatically detects regime: Trending / Ranging / Volatile Switches model behavior based on detected condition Re-trains or fine-tunes on recen...

I have a dataset that is growing quickly and a business case ready for machine-learning insights. What I need now is someone who can take the project from raw data all the way to a production-ready model: that means designing the data pipeline, choosing and training the model, fine-tuning for accuracy and latency, then packaging everything for a reliable, scalable deployment. Here is what success looks like for me: • A repeatable pipeline (Python, SQL, Airflow or equivalent) that ingests the source data, performs cleaning / feature engineering, and stores curated tables. • Well-documented training notebooks or scripts using standard frameworks (scikit-learn, TensorFlow or PyTorch) together with clear evaluation reports. • Fine-tuning that pushes performance to an agr...

I have a dataset made up entirely of categorical variables and I want to understand the hidden relationships inside it. The task is strictly exploratory: I am not asking for predictive modelling, only a deep dive that surfaces meaningful patterns and trends. What I expect from you • Clean the data where needed so that the exploratory work is reliable. • Use suitable techniques for categorical exploration—cross-tabulations, chi-square tests, association rules, clustering on encoded variables, or any other method you feel is insightful. • Present the findings in clear, non-technical language supported by concise visuals (bar charts, heat-maps, mosaic plots or similar). • Provide a short, well-commented notebook or script (Python with Pandas, NumPy, SciPy, s...

I need an AI Expert to help me in my Project, within a month. I have carried out the Analysis part of the Project. The AI person needs to recommend a relevant Model and help with 'how to do' part. This is based on a medical istrument performance analysis.

I have a sizable dataset that first needs to be cleanly extracted and then thoroughly analyzed. Because the information comes from multiple sources, I will provide a mix of Excel/CSV tables, a small hosted database dump, and several raw text exports. Your role starts with consolidating these inputs into a single, well-structured dataset, handling any duplicates or inconsistencies along the way. Once the data is tidy, I would like meaningful insights that help me understand underlying patterns. I’m especially interested in spotting emerging trends, assembling a clear, reader-friendly report, and—if the data supports it—building a simple predictive model that I can run again in the future. Please outline the statistical or machine-learning techniques you feel are most appr...

This assignment is a hands-on data assessment and evaluation. It exposes you to the various steps that data analysts go through when they receive a dataset. This is an individual assignment. Each student is expected to complete the assignment and submit their own work. Assignment Deliverable The submitted report should include a detailed discussion of the techniques you used to answer each question (see below). Include only relevant graphs and tables along with a thorough interpretation of each. Graphs and/or tables with no explanation/interpretation will not be graded. Hand in your work in a Word or PDF format. Dataset for the Assignment Download the (see attached file) It has a sample size of 70. Assignment Objective The main objective of this assignment is to develop a better under...

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. The People Analytics team at Optum provides insights and perspective on our employees and workforce trends that allow us to fulfill our mission to help people live healthier lives and to help make the health system...

25. 1、 Title: Research on an Explainable Model of the Impact of Intracranial Artery Plaque Characteristics and Burden Based on High-Resolution Vessel Wall Imaging on Cerebral Tissue Perfusion(Need to combine information)  2、 Journal partition: SCI q2 3+OA journals I need you to match 3-5 journals based on my topic, and I may submit them based on the journals you provide me with in the future, 3、 Writing requirements: Write according to my paper title and journal requirements, and provide necessary journal requirements documents, including an AI plagiarism report Turnitin (Artificial Intelligence) (1) Word count: 5000-8000 words (2) Formulas and symbols: cannot exist in image format, nor can they be created using Word's formula editor. Please format all formulas using MathType to ensu...

Pro java & springboot developer Comfortable with AI and LLMs etc

I have a dataset containing demographic details, job performance records and results from employee-engagement surveys. Your task is to turn this raw information into a reliable attrition-prediction pipeline. Work starts with careful cleaning and preprocessing: handle missing values, encode categorical variables, standardise or normalise where needed and document every step so the workflow is fully reproducible. A brief exploratory analysis should follow to highlight key attrition drivers and verify data quality before modelling. For the classifier, I’d like you to focus on K-Nearest Neighbours. If you find that another algorithm beats KNN convincingly, feel free to present the comparison—but please include KNN in the final report. Train, tune and validate the model, then eval...

I need assistance with multiple regression analysis using JASP. The data is from a survey and involves an ordinal dependent variable with 3-5 independent variables. Requirements: - Proficiency in JASP - Experience with multiple regression analysis - Ability to interpret and present results clearly Ideal Skills: - Statistical analysis expertise - Familiarity with survey data - Strong analytical skills Please provide a sample of similar work done.

25. 1、 Title: Research on an Explainable Model of the Impact of Intracranial Artery Plaque Characteristics and Burden Based on High-Resolution Vessel Wall Imaging on Cerebral Tissue Perfusion(Need to combine information)  2、 Journal partition: SCI q2 3+OA journals I need you to match 3-5 journals based on my topic, and I may submit them based on the journals you provide me with in the future, 3、 Writing requirements: Write according to my paper title and journal requirements, and provide necessary journal requirements documents, including an AI plagiarism report Turnitin (Artificial Intelligence) (1) Word count: 5000-8000 words (2) Formulas and symbols: cannot exist in image format, nor can they be created using Word's formula editor. Please format all formulas using MathType to ensu...

I'm seeking an experienced developer to write a research paper on Leveraging Virtual Reality (VR) to Enhance Efficiency, Cost-Effectiveness, and Capability Development in U.S. Air Force Acquisition. Outline listed below Research Question/Topic (Draft – Please update). How can VR-enabled digital twins and simulators enhance efficiency, cost-effectiveness, and capability development in U.S. Air Force Acquisition? To what extent can VR-based mission scenario simulations align acquisitions decisions with operational requirements and increase mission effectiveness? Systems Development & Prototyping • Virtual Prototyping for Faster Procurement: Leveraging VR digital twins to visualize, test, and refine aircraft, weapons systems, or software before production. • VR for ...

SOLO HISPANOHABLANTES Necesito apoyo puntual para un trabajo universitario que debo desarrollar en R Studio. Los datos con los que trabajaré son numéricos y el objetivo es extraer información clara mediante análisis descriptivo. El entregable debe incluir: • Medidas de tendencia central (media, mediana, moda). • Medidas de dispersión (varianza, desviación estándar, rango). • Distribuciones de frecuencias con tablas y gráficos básicos en ggplot2 o herramientas nativas de R. También requiero: – Código bien comentado en un script .R para que pueda reproducir cada paso. – Breve informe en PDF o Word explicando los resultados y su interpretación académica. – Ses...

Customer Churn Analysis & Prediction Project Overview Conducted an end-to-end Customer Churn Analysis project to identify patterns and predict customer attrition. Focused on both data exploration (EDA) and machine learning modeling to generate actionable business insights. Aimed to help businesses reduce churn, improve customer retention, and increase profitability. Dataset Details Dataset includes customer demographic, financial, and behavioral features: RowNumber, CustomerId, Surname CreditScore, Geography, Gender Age, Tenure, Balance NumOfProducts, HasCrCard, IsActiveMember EstimatedSalary Target Variable: Exited (Churn Status) Tools & Technologies Python Libraries: pandas, numpy (data processing) matplotlib, seaborn (data visualization) scikit-learn (ML modeling) Advanced Te...

I am preparing a quantitative study on “Inequality in participation versus visibility in online communities” . The raw material will come from one or more publicly-available Kaggle datasets; the challenge is to turn those data into a coherent, publication-level research project. Here is what I need from you: • Help me locate or combine the right Kaggle datasets, then document the download and preprocessing steps (Kaggle API, Python pandas, or R tidyverse are fine). • Define robust operational metrics for participation (e.g., post frequency, comment depth) and visibility (e.g., up-votes, follower counts, ranking on leaderboards). • Build the analysis pipeline—cleaning scripts, exploratory statistics, and the main inferential models (regression, GEE, or...

Hi, I am looking for a quantitative analyst or researcher who has an active Pro or Premium account on Before applying, please confirm that you already have a paid subscription and that you actively use the platform in your research or strategy development. Thank you.

Job Title: Build Bond Price Research System Using BigQuery and Machine Learning Job Description: We are seeking an experienced freelancer to develop a Bond Price Research System based on client requirements. Commbined with Machine Learning to enable powerful search, analysis, and insights into bond prices. Project Scope: - Design and build a scalable research platform for searching and analyzing bond price data (government bonds, corporate bonds, etc.). - Store and query large volumes of historical and current bond data in BigQuery. - Integrate Machine Learning models to support price analysis, trend detection, forecasting, and other research features. - Customize the solution according to the client’s specific needs. Key Requirements: 1. Technical Skills (Required): - Strong...

I have just 700 indoor photos that must be labelled for an my project upcoming object-detection model. Every visible person and every seat that is currently occupied needs its own bounding box, and because the network will train on oriented-bounding-box (OBB) data, the rectangles have to follow the exact rotation of the body or seat—especially when someone is leaning. Data is of infrared camera of a cinema check samples , please note there can be many people in one image i want each to be marked properly You will work inside the simple browser-based annotation tool I built for this purpose or any other annotation tool you like. drag the box corners, spin the angle handle where needed, hit save, and move to the next frame; the app tracks progress automatically so nothing is missed....

Do the following Stock Research Agent with SEC API and Weaviate RAG More information in the site

I want to build a custom large-language model that goes beyond text-only chat. The goal is a predictive engine that can read free-form text, combine it with numerical features, and return forward-looking insights. In practice that means designing an architecture able to embed and fuse both modalities, training it on my mixed dataset, and validating that the model can reliably forecast the target variables we care about. You will take me from data preprocessing through to an inference-ready checkpoint. I expect clean Python code (PyTorch or TensorFlow), sensible use of the Transformers or similar libraries, and a clear explanation of why each modelling choice was made. Please include evaluation notebooks that show the lift over conventional baselines and provide an API-style script so I ca...

Do the following Stock Research Agent with SEC API and Weaviate RAG More information in the site

I have just 700 indoor photos that must be labelled for an my project upcoming object-detection model. Every visible person and every seat that is currently occupied needs its own bounding box, and because the network will train on oriented-bounding-box (OBB) data, the rectangles have to follow the exact rotation of the body or seat—especially when someone is leaning. Data is of infrared camera of a cinema check samples , please note there can be many people in one image i want each to be marked properly You will work inside the simple browser-based annotation tool I built for this purpose or any other annotation tool you like. drag the box corners, spin the angle handle where needed, hit save, and move to the next frame; the app tracks progress automatically so nothing is missed....

**Project Brief: Survey Data Analysis Using MAXQDA** I am looking for an experienced researcher/data analyst to support a large-scale survey analysis project. **Scope of Work:** * Total of **50 survey datasets** * Each dataset contains responses from **100 participants** * Analysis must be conducted using **MAXQDA** * For each dataset, you will: * Perform qualitative/quantitative analysis * Identify key insights, themes, and patterns * Deliver a **3–4 page summary report** highlighting key findings **Deliverables per Dataset:** * MAXQDA project file (if applicable) * A structured **3–4 page report** including: * Key insights * Patterns/trends * Relevant interpretations **Compensation:** * **$250 per dataset analysis** * Payment will be structured into **2 m...

I am looking for a programmer or a development team with proven experience in building an intelligent KPI system and a decision support platform, based on data analysis and smart interactive presentation that helps management read performance, understand trends, and make better decisions. The project includes developing a system with 30 to 40 indicators, along with smart dashboards, practical analytics, and the use of AI for forecasting, analysis, and highlighting recommendations. Application Requirements: *** The proposal must begin with the word “Reviewed”. Any proposal that does not include samples of similar previous work will not be considered. The response should begin with a sentence that reflects actual understanding of the project details. Please clarify the propose...

I need an experienced Natural Language Processing specialist to build a predictive model that learns from text data and produces accurate, repeatable forecasts. The project centers on end-to-end model creation: cleaning and preprocessing raw text, selecting the right architecture, training, and evaluating performance against clearly defined metrics. I will supply the text dataset along with the target variable I want predicted. You will decide on the most suitable NLP approach—whether that’s classical techniques with scikit-learn or a deep-learning stack such as TensorFlow or PyTorch—document your reasoning, and implement the solution in clean, well-commented Python. Deliverables: • Reproducible code (Jupyter notebook or .py files) with setup instructions • ...

Hi I will share the details with the shortlisted candidates. Thanks

I need a hands-on Proof of Concept that lets me judge whether an AI/ML solution is worth scaling up. The PoC must move beyond slides and theory: I want code I can run, metrics I can inspect, and a short demo that shows the idea in action. My current inclination is to explore a Reinforcement learning approach, so the prototype should revolve around that paradigm—state definition, reward engineering, training loop, and performance benchmarking. If you believe a hybrid or alternative method will surface better insights, explain why and we can adjust. Scope of work • Clarify business and technical goals with me at the outset. • Prepare an appropriate sample dataset or simulated environment, documenting any assumptions you make about data generation or cleaning. •...

We need people to participate in our new idea. Anyone who contributes positively will receive a financial reward. It is a monthly competition with a prize of 10 USD. The idea is a digital project aimed at exploring future possibilities by posing interactive questions across multiple fields such as technology, medicine, and education. The project engages the public through voting on the feasibility of these ideas—whether they are achievable or impossible. It then leverages artificial intelligence to transform these visions into visual content, such as videos, offering either realistic or imaginative depictions of how these ideas might evolve in the future. The project focuses on fostering critical thinking and stimulating discussions about the impact of technology on human life, wh...