Ciencia de datos Jobs

We’re an AI-first team building modern clinical data workflows at the intersection of pharmaceuticals and AI. We’re seeking an experienced CDISC consultant to enable and mentor our internal team in Pune to build oncology SDTM and ADaM from EDC data, using R only. This is an expert-guidance role (standards, reviews, and coaching), with hands-on support to help the team become self-sufficient. What you’ll do (expert + enablement) Act as the SDTM/ADaM oncology SME for the internal Pune team. Define a repeatable, scalable EDC → SDTM → ADaM approach: standards, templates, conventions, traceability. Create/review: SDTM mapping specs (EDC → SDTM domains/variables) ADaM derivation specs (ADSL + key efficacy/safety ADaMs) QC/validation checks and common issue...

We’re an AI-first team building modern clinical data workflows at the intersection of pharmaceuticals and AI. We’re seeking an experienced CDISC consultant to enable and mentor our internal team in Pune to build oncology SDTM and ADaM from EDC data, using R only. This is an expert-guidance role (standards, reviews, and coaching), with hands-on support to help the team become self-sufficient. What you’ll do (expert + enablement) Act as the SDTM/ADaM oncology SME for the internal Pune team. Define a repeatable, scalable EDC → SDTM → ADaM approach: standards, templates, conventions, traceability. Create/review: SDTM mapping specs (EDC → SDTM domains/variables) ADaM derivation specs (ADSL + key efficacy/safety ADaMs) QC/validation checks and common issue...

I have a sizeable set of consumer-level data that needs to be examined with a clear, methodical approach. My priority is rigorous data analysis that turns raw records into well-supported insights I can act on right away. What I will provide • A cleaned CSV export and the associated data dictionary. • Context on how the data was collected and any known limitations. What I need from you • Exploratory and statistical analysis that highlights key patterns, correlations, and anomalies. • A concise written summary (PDF or Google Doc) explaining findings in plain English. • A set of reproducible notebooks or scripts (Python, R, or SQL—whatever you prefer) so I can rerun the analysis later. • Optional but welcome: clear, quick visual snapshots (charts ...

[Summary] We are seeking a Principal Data Scientist / Applied Optimization Consultant to assist in defining optimal residential designs for the Los Angeles market. The consultant will leverage data-driven approaches, integrating market data, zoning constraints, and optimization models to inform design and maximize market fit. [General Information] The project focuses on expanding into the Los Angeles market, characterized by high demand and complex regulatory and physical constraints. The goal is to shift from intuition-driven to data-driven design processes. The consultant will integrate multiple datasets, build constraint-based optimization models, and conduct scenario analyses to derive actionable design recommendations. [Tasks and Deliverables] - Integrate diverse datasets, including...

1. Task In this assignment, you work with similar scenario as in Exercise Overlay analysis: The city of Falun is known for the thousand-year-old mining operations in the Falu Mine, now a UNESCO World Heritage Site. It is estimated that there are ten million tons of mining waste in and around the city of Falun. As a result of the millennium-long mining activities, many square miles around the urban area contain high levels of metals, particularly lead. The map below shows areas where lead concentrations in the soil exceed 300 and 700 mg/kg TS, respectively. Considering the scenario above, you need to produce the following: a) Calculate the size of the area (in square kilometers), where lead concentrations exceed than 300 mg/kg TS b) Create a map showing the area of the city of Falun, where ...

Freelance AI & Predictive Maintenance Expert (Vibration Analysis) We are looking for a specialized Data Scientist or AI Engineer to develop a Predictive Maintenance solution for a critical production line. The project involves analyzing vibration data from a high-capacity main electric motor to identify early signs of mechanical failure and optimize maintenance cycles. Technical Context Data Source: High-frequency vibration data collected via IFM sensors. Dataset: Approximately 300,000 rows of historical records stored in a SQL database. System Focus: Rotating machinery (Main Drive Motor) within an industrial manufacturing environment. Core Goal: Implement an anomaly detection and health-scoring model to prevent unplanned downtime. Key Responsibilities Data Engineering: Extract, ...

Python Developer – GC-MS Data Analysis & Automated Flavor Recipe Generation System Project Overview We are a flavor manufacturing company developing an internal AI-driven GC-MS automation system. The goal of this project is to: Process GC-MS peak data Match peaks with compound libraries Identify possible natural/synthetic sources Detect marker compounds Estimate ingredient combinations Automatically generate optimized trial recipes (normalized to 100%) This is NOT a simple chatbot or automation project. This is a scientific data processing and algorithm development project. Responsibilities Parse GC-MS peak lists (CSV / Excel exports) Implement compound matching logic (CAS-based matching) Normalize peak area percentages Develop similarity scoring algorithms Ident...

We are seeking a data analyst familiar with AI tools to integrate various data systems, including Snowflake, Looker, Hex, Argo, Airflow, and SQLMesh. The goal is to create a data model ready for natural language queries. The ideal candidate will have experience in data integration and modeling, with a strong understanding of AI tools and their applications in data analysis.

I need a detailed two-dimensional hydraulic model to evaluate flood behaviour across a predominantly rural catchment. The model will be used exclusively for flood risk assessment, so accuracy in simulating overland flow paths, storage areas and channel–floodplain interaction is essential. I will supply topographic data, land-use information and historical flow records; you will assemble, calibrate and run the model in the 2-D module of a recognised engine such as HEC-RAS, TUFLOW, Iber, MIKE 21 or a comparable industry-standard package. Please let me know up front which platform you prefer and why, as I need to be able to review and possibly re-run scenarios later on. Deliverables • Geo-referenced flood extent maps for at least the 10-, 50- and 100-year events • Raster o...

I need a well-structured research proposal that investigates how artificial intelligence can cut the environmental footprint of transportation within e-commerce logistics. The document must clearly identify the current challenges of last-mile and line-haul delivery, map the latest AI-driven solutions that address them, and articulate a research methodology capable of testing their impact on carbon emissions, fuel consumption, or related sustainability metrics. Please ground the study in recent, peer-reviewed literature and authoritative industry reports, focusing on transportation methods such as electric or automated vehicles, dynamic route-optimisation algorithms, and predictive demand planning. While my priority is reducing environmental impact including Carbon emission, links to opera...

Autonomous AI agent I want help creating a self-directed AI agent that can tackle biological/medical research research by reviewing the literature and creating mathematical models of disease pathology using the R programming language. • Perform comprehensive literature reviews by ingesting and summarising peer-reviewed papers from major scientific journals and pre-print servers. • Analyse data pulled from public repositories • Reproducing models in the literature and coming up with new hypotheses for mathematical models of disease. I expect an end-to-end workflow: automated retrieval of journal articles and database records, semantic search across that corpus, data cleaning, exploratory and confirmatory analysis in R/mrgsolve, and an LLM-driven (Claude) reasoni...

I’m building a unsupervised classifier that learns jointly from audio recordings and accompanying physiological signals. My end-goal is a robust prediction model that can generalise to new subjects, so every modelling choice—from feature pipeline through network architecture and hyper-parameter search—has to be evidence-driven and reproducible. Here is what I already have: raw multichannel wave files, synchronised physiological traces (ECG, EDA and respiration) and a draft protocol for train-test splits. What I still need is the deep-learning firepower to turn this into a working model, coded cleanly in Python with TensorFlow or PyTorch, complete with training scripts, inference wrapper and clear documentation. I’ll share the data dictionary, baseline metrics and ...

I need a trainer to teach Machine Learning to college students in India. Key Requirements: - Comprehensive coverage of ML concepts - Hands-on projects and real-world applications - Interactive sessions with Q&A Ideal Skills: - Expertise in Machine Learning - Experience in teaching/training - Strong communication skills - Background in working with college students

ob Title: Data Scientist Role Overview: We are seeking a Data Scientist to help us transform our CRM, Gradlynk, into a more intelligent, AI-driven platform. The role will focus on leveraging data to enhance student engagement, improve learning outcomes, and optimize operational efficiency across our edtech ecosystem. Key Responsibilities: -Collect, clean, and analyze data from Gradlynk and other sources to generate actionable insights. -Develop predictive models and machine learning algorithms to personalize student experiences and forecast performance trends. -Collaborate with IT, Product, and Operations teams to integrate AI-driven features into Gradlynk. -Translate complex data findings into clear recommendations for educators, administrators, and business stakeholders. -Monitor an...

I need a solution to detect the presence of solar panels on existing roofs using satellite images. The primary analysis required is basic presence detection. I also need the addresses of each building to be able to send them mail regarding their solar panels. Requirements: - Detect solar panels using satellite imagery - Provide analysis on the presence of solar panels Ideal Skills and Experience: - Experience with image analysis and machine learning - Proficiency in handling and analyzing satellite images, especially in formats like GeoTIFF - Familiarity with GIS software would be an advantage Please provide guidance on the satellite images required for this task. Pilot project starting in community of Tuscany in Calgary, Alberta, Canada. There are about 6,500 buildings. We want to st...

ob Title: Data Scientist Role Overview: We are seeking a Data Scientist to help us transform our CRM, Gradlynk, into a more intelligent, AI-driven platform. The role will focus on leveraging data to enhance student engagement, improve learning outcomes, and optimize operational efficiency across our edtech ecosystem. Key Responsibilities: -Collect, clean, and analyze data from Gradlynk and other sources to generate actionable insights. -Develop predictive models and machine learning algorithms to personalize student experiences and forecast performance trends. -Collaborate with IT, Product, and Operations teams to integrate AI-driven features into Gradlynk. -Translate complex data findings into clear recommendations for educators, administrators, and business stakeholders. -Monitor an...

Aura Institute of Training Excellence, Chennai, is a growing technical skill development institute focused on delivering industry-oriented training programs for students and working professionals. We are currently looking for Technical Trainers for the following programs: Data Science & Machine Learning Full Stack Web Development (MERN / MEAN) Cybersecurity & Ethical Hacking Cloud Computing (AWS / Azure / GCP) Artificial Intelligence & Generative AI

I need structured, beginner-friendly coaching that will take me from “hello world” to employable in Natural Language Processing. My goal is to understand core NLP concepts, build a small portfolio of projects, and feel confident discussing them in interviews. I already code a little in Python but have no formal NLP background. I’d like to cover the foundations—tokenisation, embeddings, transformers—then progress to hands-on mini-projects using libraries such as spaCy, Hugging Face, TensorFlow or PyTorch. Guidance on best practices for data preprocessing, model selection, evaluation and error analysis is essential, along with tips on how to present this work in a résumé or GitHub repo. Deliverables I have in mind: • A personalised learning ...

I'm looking for an experienced developer to create an algorithmic trading bot for trading stocks using the Alpaca API. Key Requirements: - Implement algorithmic trading strategies - Trade exclusively in stocks - Use of Python programming language Ideal Skills and Experience: - Proficiency in Python - Experience with Alpaca API - Strong background in algorithmic trading - Familiarity with financial markets and stock trading Please provide examples of similar work done and your approach to this project.

I need an LLM to assist with code completion in R, specifically for mathematical modeling tasks. Key requirements include: - Familiarity with LLM integration for code completion -Biology experience -Not too much coding and LLM experience required but asking for a learner that is good at organizing thoughts and data and taking initiative Ideal skills and experience: - Strong background in R -experience with mathematical modeling -experience with biological research - Prior experience using language models for coding tasks

I’m ready to turn a fresh idea into a working MVP and need an AI specialist who can own the end-to-end predictive analytics layer. The single most important outcome is a model that takes my existing data, produces reliable forecasts, and is simple enough to slot straight into a lightweight product demo. Here’s the scope in plain words: • Select and train an algorithm that balances accuracy with speed—feel free to use Python, TensorFlow, PyTorch, or another framework you prefer, so long as the environment is reproducible. • Wrap the model in a small REST or GraphQL API so I can call predictions from a basic front-end. • Hand over deployment instructions for a cloud environment (AWS, GCP, or Azure—your choice) so the MVP runs in a real setting, n...

I'm looking for a skilled machine learning expert to help with my final year university project. The goal is to identify different sleep stages using multimodal data, specifically ECG patterns and blood pressure signals. Key Requirements: - Analyze ECG and blood pressure data - Develop a machine learning model to estimate sleep stages - Utilize existing dataset Ideal Skills and Experience: - Strong background in machine learning - Experience with ECG and blood pressure signal analysis - Proficiency in data processing and model development - Familiarity with sleep stage identification techniques

Sto avviando un progetto di intelligenza artificiale pensato per gestire e ottimizzare i processi di marketing e vendite. Cerco una figura capace di: • Analizzare i dati esistenti (CRM, campagne, fatturato) per individuare pattern rilevanti. • Automatizzare attività ripetitive, come l’invio mirato di e-mail o la profilazione dei lead. • Generare insight in tempo reale che guidino le decisioni commerciali. • Fornire previsioni sull’andamento delle vendite e sull’efficacia delle iniziative di marketing. Mi interessa una soluzione funzionante end-to-end: dal reperimento e pulizia dei dati alla messa in produzione del modello, con dashboard di reportistica chiara e documentazione di utilizzo. Preferisco tecnologie consolidate (Python, scikit...

I have a research paper in development and want to elevate it to publication-ready quality. I’ll provide you with the current manuscript, my notes, and any supporting data; what I need back is a version that reads clearly, is backed by up-to-date sources, and meets the formatting and citation standards of high-impact journals.

I need to optimize the website SEO and also google ads. I want to hire professionals only

I'm looking for an AI-driven building automation energy analyzer tailored for commercial buildings. The system should have the capability to upload comprehensive building databases and trend files in CSV, Excel, JSON, or Zip formats. Key Requirements: - Analyze overall energy consumption and efficiency ratings - Provide insights on kW consumption versus energy savings - Identify faulty equipment and potential energy savings Ideal Skills and Experience: - Expertise in AI and machine learning - Strong background in energy analysis and building automation systems - Proficiency in handling and analyzing data in CSV, Excel, and JSON formats - Experience with commercial building energy metrics BAS System examples - WebCtrl -Honeywell Niagara -Tridium -Seimens -Alerton Once the database...

Hello! I already have a working Python-based trading bot and I’d like an experienced developer to take it to the next level. The bot is fully functional and production ready, I don’t want to change the core structure because it is made for upstox algo. Now I just need help in swapping since I'm getting difficulties in expertise to swap strategy. I'll share the more details and bot over chat. Thanks!

I need a working proof-of-concept that hardens my wireless network by analysing live traffic and flagging hostile activity the moment it appears. The model must reliably catch the attacks that worry me most: Denial of Service (DoS), Man-in-the-Middle (MitM) intrusions, classic packet sniffing, and ARP spoofing. Everything has to run in real time on a modest on-prem machine, so efficient feature extraction and lightweight inference are a priority. The task breaks down naturally into three parts. First, capture and label representative WLAN traffic—public datasets are fine as a starting point, but I also want a small tool that lets me pipe raw pcap streams into the training set so the system can learn my network's quirks. Second, build and train the detection engine: a well-comme...

I am looking for a tutor who can help me understand, in a comprehensive and step-by-step manner, how to deploy a production-ready dashboard that displays the results of a model. My current stack includes: Google Cloud Platform (GCP) Vertex AI Workbench (where I trained the model) Streamlit (for the dashboard) Git and GitHub (for version control) I already have: A trained model in Workbench The .py files developed A structured and synchronized GitHub repository The intention to deploy everything in GCP However, I am not only looking for help with deployment — I want to fully understand the technical process behind it, including: How to properly structure the project for production. How to connect the trained model to the dashboard. The best architecture choice in GCP for...

I need a working, proof-of-concept framework that ingests live and historic network traffic logs, learns from them in near-real time, and flags malicious patterns before they escalate. The core must combine traditional threat-intel techniques with machine-learning pipelines so the system continuously adapts as new data arrives. Here’s what success looks like to me: • A modular data-collection layer that can stream pcap, NetFlow, or similar log formats into a preprocessing engine. • Feature-engineering and model-training code written in Python (feel free to leverage Pandas, scikit-learn, TensorFlow, PyTorch—whatever best suits the task). • A detection component that scores incoming traffic and raises alerts via a simple REST API or CLI output. • Cl...

I have several large RNA-seq datasets from TCGA covering multiple cancer types, and I need a focused survival analysis that links gene-level and gene-set activity to overall and progression-free survival. All raw counts, FPKM tables and the matched clinical files are already in place; what I require is the analytical workflow and an interpretable report. Here is the workflow I would like you to follow: • Pre-process and normalise the RNA-seq count data, matching each sample unambiguously to its clinical record. • Build Kaplan-Meier curves and multivariable Cox proportional-hazards models to identify genes whose expression significantly associates with survival outcomes, adjusting for key covariates (age, stage, subtype, etc.). • Run GSEA (Gene Set Enrichment Analysis) ...

I need an expert to develop predictive models using AI on airway assessment parameters for my research thesis. The project needs to be completed within a month. Key Requirements: - Expertise in AI and machine learning - Experience with predictive modeling - Familiarity with healthcare data, especially airway assessment parameters - Strong analytical skills Ideal Skills and Experience: - Background in data science or related field - Proficiency in programming languages such as Python or R - Experience with AI tools and frameworks - Ability to interpret and visualize complex data Please provide a portfolio with relevant experience.

I am seeking an ML engineer/researcher to prepare a Q1-level scientific manuscript (Scopus + Web of Science) in the domain of eHealth / Clinical Decision Support Systems (CDSS) using ML/DL on MIMIC-IV (PhysioNet) data. Outcome: manuscript “ready for submission” + a complete technical report detailing all stages + reproducible code/notebooks. Journals (client candidates) Candidates (you may propose the best option or an alternative with justification of fit): 1)MDPI AI (ESCI WoS + Scopus) 2)Journal of Information and Telecommunication (ESCI WoS + Scopus) 3) Array (Elsevier) 4) IEEE Access 5) Big Data Mining and Analytics (IEEE) Task for the contractor: choose 1 target journal and tailor the problem formulation/structure/length/format strictly to the “Guide for Authors,&rd...

I’m launching a focused pollution-control study on local waterways and need a researcher who can turn scattered information into a clear, evidence-based picture of what is really happening beneath the surface. The core of the job is data: finding it, validating it, analysing it and turning it into insights decision-makers can act on. You will help me locate and compile raw water-quality figures—field samples, public monitoring stations, satellite or drone readings, academic papers, anything reputable—then clean and merge those datasets in a way that lets us spot patterns of contamination over time. Solid skills in Excel, Python or R for data wrangling, plus basic GIS mapping to visualise hotspots, will be essential. Once the numbers are in shape, I’ll rely on you ...

I need a researcher who can build a production-ready model that listens to a baby’s cry, watches the paired video, and decides—reliably—whether the cause is hunger, discomfort, or simple attention seeking. Audio and video must be fused inside one architecture; running them in parallel but independently will not satisfy our accuracy goals. You may use the deep-learning stack you trust most (PyTorch, TensorFlow, Keras, OpenCV, torchaudio, etc.) provided the final network can run in real time on an edge device and be exported to ONNX or TFLite. I will share product constraints and a small proprietary data set; you will expand it through public sources or augmentation, perform rigorous cross-validation, and refine the model until we consistently exceed 90 % precision and rec...

I am writing to inquire whether you would be available to provide statistical support for a prospective research project I am currently conducting. The study is complete in terms of data collection and laboratory analysis, and I am now seeking guidance on the most appropriate statistical analyses and interpretation. Project title: Reference intervals for FIBTEM measurements using the ROTEM® gamma device in healthy dogs compared to fibrinogen concentration measured by the Clauss assay. Study objectives: 1. To establish reference intervals for FIBTEM parameters obtained using the ROTEM® gamma device in healthy dogs. 2. To assess the clinical acceptability of these reference intervals compared to fibrinogen concentration measured by the Clauss assay. Dataset overview: The dataset i...