Data Science Jobs

The statistical groundwork is finished: 106,000+ football matches and more than 48 million individual odds movements are already structured, cleaned, and sitting in Python-ready data stores. What I need now is a fresh layer of intelligence that can group the patterns and pick up on the regime shifts as they occur —specifically, to surface the hidden structures that govern betting-market behaviour. This regime detection will challenge you immmensely but also matering it can provide enormous opportunity - are brave enough and smart enough to challenge the status quo?We have all the ground work laid and there is no statistical obvious deviation that favors the bet placer ONLY the BOOKIE over 106K of matches - and recent one months anlaysis - there is no ground work to be done only for y...

I'm seeking an expert to help with a research paper on AI/ML in healthcare to get published in IEEE conference as well as reputed journals Key requirements: - In-depth knowledge of AI/ML, especially in predictive analytics. - Experience with healthcare datasets, particularly patient medical records. - Strong research and writing skills. Ideal skills include: - Good research profile. - - Ability to present complex ideas clearly and concisely.

Post a table and a graph for: Real GDP and Nominal GDP together so you can visualize the difference and the trend. Describe the trend. For example: GDP increased all years, GDP grew more during the first n years and then dropped...? If there are important dips in GDP provide a possible reason. Real GDP Growth. Describe the trend. Did the economy experienced a recession? Which year(s)? Gini Coefficient. Describe the graph: income distribution got better/worse/same? provide a possible reason. Remember a lower GINI coefficient represents a better/ more equal income distribution. Nominal GNP and Nominal GDP. Compare GNP to GDP: is GNP larger/ smaller/ same as GDP? If different, why do have different values for the same country? National Income. Include all components (Wages, Interest, Rent, Pr...

I'm looking for a senior developer with hands-on experience defeating Arkose Labs FunCaptcha (specifically the newer game variants such as hopscotch_highsec / hopscotchv3) in a headless / API-based pipeline. ▎ ▎ I already have a working Node.js codebase that: ▎ - Mints Arkose tokens via a real-Chrome TLS client (bogdanfinn) ▎ - Rotates residential proxies + BDA fingerprints per attempt ▎ - Uses commercial classifiers (YesCaptcha, OmoCaptcha, ) ▎ ▎ The pipeline reaches the challenge-submit step consistently, but the classifiers we use are giving low-accuracy answers on the newer navigation-style variants, so we're getting solved:false on the final wave. ▎ ▎ What I need help with: ▎ - Diagnosing whether the failure is truly answer-quality vs a deeper trust/suppression issue ▎ - Imp...

NOTE: This is purely intellectual partnership. Money is not a motivation in this project. Seeking an established researcher for long-term collaboration in computational/structural biology. Applicants focusing solely on "Thesis Writing" or similar services will not be considered. Requirements: * PhD in CS, computational science, bioinformatics, statistics, or related field * Established publication record * Professional standing to serve as a future academic/industry referee Collaboration: * Strengthen methodology and experimental design * Perform supplementary analyses * Co-write manuscripts and reviewer responses * Provide a reference letter after an established collaboration Full co-authorship for contributions meeting authorship standards, with opportunities for follow-u...

i would like to know is there anyone that can get the source code of pinescript on tradingview which is hidden ?

Sessions will revolve around linear algebra, calculus, and probability as presented in the open-access text , always tying theory back to practical machine-learning use-cases. I am a Beginner and progress fastest through Kinesthetic (hands-on activities), so each concept should be paired with worked examples, code snippets in Python or MATLAB where relevant, and plenty of guided problem practice. What I need from you • Live, interactive lessons that unpack the core ideas behind vectors, matrices, multivariable calculus, limits, derivatives, integrals, random variables, and distributions, then connect them to algorithms such as gradient descent, PCA, and logistic regression. • Custom practice sets after every session, plus detailed walk-throughs of the solutions. • Bri...

Sessions will revolve around linear algebra, calculus, and probability as presented in the open-access text , always tying theory back to practical machine-learning use-cases. I am a Beginner and progress fastest through Kinesthetic (hands-on activities), so each concept should be paired with worked examples, code snippets in Python or MATLAB where relevant, and plenty of guided problem practice. What I need from you • Live, interactive lessons that unpack the core ideas behind vectors, matrices, multivariable calculus, limits, derivatives, integrals, random variables, and distributions, then connect them to algorithms such as gradient descent, PCA, and logistic regression. • Custom practice sets after every session, plus detailed walk-throughs of the solutions. • Bri...

I want to build an AI-driven module that sits alongside my existing trading setup and delivers continuous, real-time risk assessment for both the forex and cryptocurrency markets. The goal is simple: every open position and pending order should be evaluated second-by-second so I immediately see my true exposure and can take action before a drawdown spirals. Here’s what matters most to me: • Real-time risk assessment is the entire focus. Position sizing, margin usage, volatility spikes, correlation shifts, and news shocks all need to feed straight into the model so it can flag elevated risk instantly. • The first release only has to cover forex and crypto. If your architecture is flexible enough to extend into stocks later, that’s a plus but not required right now...

I need a fully-fledged, advanced-level course that dives deep into descriptive statistics and is ready for delivery as quickly as possible. The aim is to take learners who already know the basics and push them toward expert-level understanding of exploratory data analysis, high-dimensional summaries, and the latest visualization techniques. Here’s what I require: • Detailed syllabus that logically builds from core concepts (moments, shape, variability) toward multivariate and high-order descriptive measures. • Slide deck (PowerPoint, Keynote, or Google Slides) for each module, complete with speaker notes. • Practical notebooks or scripts in R or Python (your choice) that reproduce every example used in the slides. • At least two real-world datasets per mod...

I’m working through a graded assignment for my Data Science & AI course and need an expert hand with the assignment portion. The task isn’t massive, but it does require someone who can walk me through each step, provide clean, well-commented code (Python preferred), and explain the reasoning in plain language so I can confidently discuss the approach later. What I’ll need delivered: • A reproducible notebook or script that tackles the assignment requirements from data preprocessing through model evaluation • Brief inline comments plus a short write-up (one page is fine) summarizing methods, key metrics, and why those choices make sense • A quick call or chat after delivery so I can clarify any points before submission If that sounds straightforwa...

I am looking for an experienced agronomist to provide practical guidance throughout the growth and maintenance stages of my cereal crops. The main focus will be crop health, nutrient management, pest and disease monitoring, irrigation or moisture management, and maximising yield and grain quality. I will provide field history, soil-test results, crop information, and weekly scouting observations. I need these details translated into clear, practical recommendations that can be implemented in the field. The agronomist should be able to: * Analyse soil-test results and relate nutrient requirements to crop growth stages. * Recommend suitable fertiliser, micronutrient, and soil-amendment applications. * Identify potential nutrient deficiencies and crop stresses. * Establish practical pest, ...

My goal is to build an AI-driven inventory management application that keeps stock counts accurate to the second and helps me plan cash flow before problems arise. The core of the platform is real-time inventory tracking—every SKU, every location, synchronised automatically. Beyond the live view of stock, the system must: • run order management workflows end-to-end (receive, pick/pack/ship, confirm) • generate clear budget-forecast reports so I can see purchasing needs and working-capital requirements weeks ahead If predictive algorithms or machine-learning models improve the accuracy of those forecasts, please incorporate them. The finished software should be easy to use through a clean dashboard and expose a secure API for future integrations. Deliverables &b...

I’m creating a production-ready AI/ML solution that automatically reviews articles pulled from news websites and flags any item that is likely to be fake. All content will be in English, and the system must consistently reach at least 90 % accuracy on an independent validation set; precision and recall should be reported alongside overall accuracy so I can see how it performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, Tensor...

I have a growing archive of drill-hole and operational logs from our mining sites and I want a specialist to turn those raw tables and sensor feeds into clear, actionable insights that help us streamline day-to-day operations. The core focus is optimisation: I’m less interested in historical “what happened” reports and far more interested in seeing where we can tighten cycle times, cut idle hours, and schedule maintenance before downtime strikes. You’ll start by cleaning and structuring the datasets (CSV exports from fleet management systems, time-series from pressure and torque sensors, and geology logs). From there, I expect a blend of descriptive summaries to frame the current state, followed quickly by predictive or prescriptive modelling that pinpoints concret...

I have a set of drilling-related mining datasets that need to be explored specifically for trend analysis aimed at pinpointing potential anomalies. Your job is to dive into the data, surface any irregular patterns or outliers, and explain what they might mean operationally. What I will hand over: • Raw drill-run datasets in their current format (CSV / Excel); if you prefer a different format, let me know and I can convert it before we start. What I need back: • A concise, reproducible script or notebook (Python, R or similar) that carries out the full trend analysis pipeline. • Clear visualisations that highlight identified trends and the exact data points flagged as anomalies. • A short report (PDF or Markdown) summarising your methodology, the key findings, and reco...

I’m assembling a training corpus for a math-focused large-language model and need a calculus specialist to enrich selected research papers with clear, accurate explanations of every sophisticated step. You’ll read each PDF, insert concise LaTeX-formatted comments that unravel dense derivations, and flag any ambiguous notation so the model grasps the intended meaning. Deliverables • Annotated PDF (or .TEX) with inline clarifications • Companion JSON that maps each comment to its passage and supplies a one-sentence paraphrase Acceptance criteria • All non-trivial calculus moves are explained in ≤3 sentences, free of factual error • Original math notation preserved; added text compiles in LaTeX • File names and JSON keys match the template I...

I’m assembling a small, highly-skilled team of mathematics domain experts to help me refine a large-language model. Your main responsibility will be data annotation: taking raw mathematical questions, proofs, theorems, solution outlines, and related explanatory text and tagging them with the precise metadata the model needs (topic, sub-topic, difficulty level, prerequisite concepts, step-by-step reasoning, common misconceptions, etc.). Because this work directly feeds the model’s training loop and later evaluation, accuracy matters more than speed. You should feel comfortable distinguishing between, say, elementary number theory and analytic number theory, or spotting a subtle gap in a proof that could mislead the model. Familiarity with JSON-based annotation formats, Python...

We are seeking a strongly credentialed Internet research and information-retrieval specialist to conduct a comprehensive analysis of publicly available Internet content concerning a discontinued consumer product/brand that was widely marketed approximately 25–35 years ago. The objective is to determine the volume and nature of current online discussion concerning the historical brand and product. Scope of Work The research will focus on two primary questions: Extent of continuing Internet discussion and recognition. Identify and quantify publicly available Internet and social-media references concerning the historical brand/product, including consumer recollections, discussions, nostalgia, product descriptions, images, advertising references, and interest in or requests for the p...

I’m sharing a rich, multi-sensor environmental dataset and I want to see just how much actionable knowledge you can squeeze out of it. Your mission is to surface at least 35 meaningful KPIs and supporting metrics, lay every calculation bare, explain why each one matters to real-world decision-making, and wrap it all into both an interactive Excel dashboard and an accompanying analytical report. The dataset blends multiple environmental streams, so correlations, anomalies, quality indicators, and uncovering hidden patterns are all on the table. I will reward depth of thought far more than flash: half of the score is tied directly to the strength, originality, and relevance of the KPIs you define. Methodology and transparent maths account for another 20 %, clarity of presentation 20 %...