Predictive Analytics Jobs

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Fixed-Price - Expert ($$$) - Est. Budget: $1,500 - Posted
Looking to set-up a machine learning solution on AWS to predict outcomes in a dress-up game we operate. >>Background<< We have a mobile dress-up game where users need to dress up their avatar for a particular event (e.g. beach party, christmas, dinner, visit to the mall). Players choose dresses / shoes / makeup / etc from a set of options we present them. The player's composition is then submitted for voting. Voting is done by other players in the game. Voting can last for upto a day. The composition with the largest number of votes for that event, is the winner for that event. >>Problem Statement<< We want to analyze which compositions + event pair generate the top votes. Having 'learnt' these patterns, we then want an API that can be used to determine a composition's expected score, without having to wait for Voting to complete. >>Requirements<< Aside from configuring the relevant learning models, training the system, building an end-point to predict outcomes, will also include scripts / process to collect the labelled data (that is already collected in a Postgres database outside of AWS).
Skills: Predictive Analytics Machine learning
Fixed-Price - Expert ($$$) - Est. Budget: $5 - Posted
Looking for a programmer with a deep "application architecture & programming" expertise, skill sets and solid track record in developing highly specialized analytical applications. The ideal candidate should be able to demonstrate the following; 1) Deep functional working knowledge of the financial markets / industry. 2) Developed financial "investment & trading" applications. 3) Used "machine learning" and "advanced artificial intelligence". (Azure, Matlab, H2O, SParks ML, etc.) 4) Demonstrated track record using various "optimization techniques". 5) Relevant investment and trading foundation language knowledge and expertise.
Skills: Predictive Analytics Artificial Intelligence Machine learning
Fixed-Price - Intermediate ($$) - Est. Budget: $750 - Posted
Looking to build an optimization API using machine learning. The API will take a number of dimensions and based on these dimensions spit back a value. This version of the API is a proof of concept. Detailed information will be provided once we engage in this project, but for now here are some basic high level points. Some complexity to this: - The API should be able to optimize and respond with an output fairly quickly - This API will be used by multiple clients, the algo should be able to pull knowledge from a global POV (e.g. learnings from all parties) as well as specific patterns/learning from the specific client using the API (in essense it will be building a global model as well as a client specific model. However I am not sure if this provides a lot of value so we can talk about this) - Each party will have a learning period, where it will not function but monitor the data to build a model, will engage after a certain amount of data/or when a confidence level has been reached - The API should be capable of producing reports, both at a global level as well as client/more granular level - The API should quantify it's performance (i.e. provide a way of quantifying the lift the optimization is providing. this could be done via using a control group, A|B testing, etc. leave it up to you to advise) - Lets assume that the API can handle X dimensions, if the client is sending less than X dimensions, the API should still function (to the best of it's abilities). It should also be able to provide some insight into the level of improvement if all the dimensions were used - A way of testing the API/Model. the models can be built using a test data set, but there needs to be a simple testing/demo interface to display the proof of concept - There are also some future proofing for which hooks may need to be built in now, will give more details later but they include things such as control on who can use the API, what dimensions can be passed, client preferences/limitations on dimensions, etc. Here is a very basic example: Lets say our model optimizes how many oranges to buy. the client will initially tell us: how hungry they are on a scale of 1-10, how much they weight (in kg), their nationality and the time of the day. Our model will then figure out how many oranges to buy and send them a single numeric value back. Once we send them the value back, client will then tell as a yes or no that they were satisfied with the number of oranges or not. The model will take this Yes/No response to recalibrate the model for next time (this is the ML component) thats a basic example. Now if you noticed i asked for nationality and time of day, and that seems kinda strange thing to ask. The reason is, I dont know if nationality or time of day makes a difference or not, but our model (based on regression) will be able to determine if there is a relationship or not and adjust it's self based on that. In other words, there's a live optimizer stored in a server somewhere, the optimizer is based on machine learning and there are a set number/types of variables the client can send and based on these it will tell them a value. After telling them the value, the client will send a Yes/No response back that should help the model recalibrate it's self
Skills: Predictive Analytics Algorithms Data Analytics Data Science
Fixed-Price - Intermediate ($$) - Est. Budget: $75 - Posted
Hi, I’m looking for Data scientist with extensive sentiment analytics experience, I have a small training set and testing set and I need someone to build the best classification model in Python a long with explanation for each line of code The deliverables will be to python file and python note book file It should be a easy task for real expert people Thanks,
Skills: Predictive Analytics Data Analytics Data Science Machine learning
Hourly - Expert ($$$) - Est. Time: 3 to 6 months, 30+ hrs/week - Posted
Hi , I am looking a data Scientist for our mobile analytics product , please have a look at the product page www.retainlytics.com Here is what we require :- 1. The candidate should have good knowledge of building software architecture , SQL , Data interpretation and reporting 2. Candidate should have of knowledge amazon redshift , postgres SQL 3. Candidate with the knowledge of business landscape of mobile Analytics preferred
Skills: Predictive Analytics Data Analytics Data Interpretation Data Modeling
Fixed-Price - Expert ($$$) - Est. Budget: $800 - Posted
Hello, I have an accountancy app. We import in our MYSQL database, bank sheets every months for several hundreds companies (meaning, date+description+amount). I would like to do bank categorization according to a list of categories. I found some posts about people who solve the problem with naive bayes: https://github.com/cantino/reckon blog.octo.com/naivebayes/ I am looking for somebody to write a script to: - read the new lines in the table - learn from previous categorization - do the categorization and record it in the same table. On this basis, you are free to propose me any architecture or solution. Thank you.
Skills: Predictive Analytics Algorithms Machine learning Statistics
Hourly - Expert ($$$) - Est. Time: Less than 1 week, 10-30 hrs/week - Posted
We have a set of assessment data with inputs and outputs as well as a dozen or so other explanatory variables. The outputs were created using a multi-dimensional IRT model, but we don't necessarily need you to re-create that model. We would like to see if there is a simpler model that will produce similar enough results that it less computationally intensive. Ideally the model would be built in R, but we are open to other software, so long as eventually it can be re-coded in R.​ Creating a predictive model and associated errors in model in R.​ Fluent english. Expert predictive modeling skills.
Skills: Predictive Analytics R
Fixed-Price - Expert ($$$) - Est. Budget: $500 - Posted
Produce a short paper that outlines how either the latest technology, or your own technology can be used to automate the selection of a future date (booking), over the telephone using voice recognition (VR) or other methods to capture details of the booking. While aspects of this paper can be theoretical and risky, we are looking for a practical solution that can be rolled out in a lightweight form as P.O.C. within months. We use the Asterisk engine, so are looking for a VR tech thats is compatible with this. In your application, please outline at a very high level a possible approach, and provide examples of your style of research.
Skills: Predictive Analytics Artificial Neural Networks Automation Data Analytics