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Seating Chart Generator Algorithm

The proposed Seating Chart Generator will be used by event planners to optimize the seating arrangements at various firm sponsored events throughout the year. Please see attached for more information.

Legal
Customer Analytics
CRM, ERP, Accounting, Operations, Marketing Automation Tools

$2,000 - $5,000

Starts Mar 15, 2015

5 Proposals Status: IN PROGRESS

Client: B***** * ********* ***

Posted: Mar 06, 2015

Automate Financial Portfolio Management using Morningstar Data Feeds - Phase 1

We are a wealth management company that is perfoming portfilio management and asset allocation manually using Excel. We look at financial data from Mornigstar and then enter the change in prices in Excel. We would like to automate this process by creating a central data repository to bring in data feeds. This project will be executed in three phases.  The budget displayed is for Phase 1.

1. General considerations

There project will have three phases:

  1. Phase 1 - create the framework for the solution and automate the creation of the customer files based on the transactions and the data downloaded from Morningstar.
  2. Phase 2 - implement decision engine that will propose the transactions that should be performed, and will generate an output with the transactions.
  3. Phase 3 - implement an online solution where each customer can log in and see the status of his portfolio 

2. Deliverables

The proposed solution consist of the following deliverables:

  1. Database system that is storing all the data processed
  2. Morningstar connection module that periodically downloads the data from Morningstar
  3. Customer file - the module that displays the file of a customer, and can generate the output file for the customer after the values were updated based on the data from Morningstar
  4. Import module that will import in the system the portfolio changes for each customer after transactions were processed

3. Work process

The solution we provide will support the following work process in Phase 1:

  1. All the portfolio information of all the customers are imported from an Excel into the system
  2. Periodically the application downloads from Morningstar the price and the rating of different funds
  3. The portfolio of each customer is updated with the downloaded information
  4. The user calls a report for each customer and can preview the status of the portfolio
  5. From the report the portfolio information for a customer can be saved into the requested Excel format (or other format)
  6. Trades are performed on different portfolios for different customers
  7. These trades are imported into the system from an Excel file
  8. The report with the portfolio information is called again to see the updated portfolio

The benefit of this approach is that the manual work for downloading the fund information and update the portfolio files for each customer will be completely automated. What remains manual work is just to perform the transactions for each customer.

In Phase 2, the functionality can be extended so that the system will propose transactions to be performed in order to bring the portfolios to the targeted status.

4. Technology Stack

We are leaning toward technology based on Microsoft SQL Server. We will need help in procuring Microsoft SQL Server hosting with the SSIS and SSRS modules installed.

Financial Services
BI Development
Data Integration

$10,000 - $15,000

Starts Mar 06, 2015

1 Proposal Status: COMPLETED

Client: S********* ******** ****** ***

Posted: Mar 04, 2015

Multi-sided Platform Healthcare, Senior Data Architect

Data Architect with proven advice qualities. You combine in-depth and current knowledge of architectural principles - including the various platforms and tools - with a strategic vision and the ability to enthuse others before. You like to present in plain language complex insights, even to people who are less IT minded. Experience in high-volume data environments is a must. If you have gained that experience in the health care and / or multi-sided platforms, we see it as a big plus.

Else you bring with you:

  • Masters (BI, Information Science, Information Management)
  • 5+ years of relevant experience in information management and architectures
  • Persuasive communicator, strong organizational, project management skills
  • Previous successful projects on translating data in to actionable insights
Consumer Goods and Retail
Energy and Utility
Financial Services

$75/hr - $225/hr

Starts Apr 01, 2015

9 Proposals Status: CLOSED

Client: i************

Posted: Mar 03, 2015

Retirement Planning and Forecasting Application

We are a company that provides retirement planning and wealth management services.  We have been using an outdated DOS-based program to provide forecasts to our clients.  We would like to develop a simple application that will take a set of inputs and provide forecasts as outputs based on a specific logic.  While we are attaching the results that are generated for each forecast, it would be helpful for us to hire someone who has the ability to run the DOS-based program in Windows environment to reverse-engineer formulas that may be unclear.  The DOS-based program can be downloaded here: https://www.dropbox.com/s/jdho2uxftdqk0lz/qpro.zip

Here are the different types of forecasts that we are currently running and their examples are attached. The pdf file names correspond to the executable files in the pps1 folder within the zip file.

Retirement Funds Forecaster (see attachment RCP1.pdf)

Column A = Client expenses.  Relatively simple calculation, The expense grows by whatever inflation number we choose to use.  In this case it is 4.00%.  The only issue here is that a mortgage, car payment, long term care premium won’t inflate so I manipulate the cells to take the cell above $6820, subtract out the mort payment or LTC premium, multiple the net number by 4.00% and then add the mort and LTC premium back in and replicate the process each year until the mort is paid off.  Sometimes I will have to add on an expense such as a tax increase which will then flow through the following expenses.

Column B = monthly savings.  Used when client is still working and has 401(k), company match  and or surplus from income.  This grows at whatever rate we choose.

Column C = social security for each spouse if married – we choose to grow at 3.00% but should be any rate we choose.

Column D = pension column, same as social security, grows at whatever rate we choose if any.  This column needs to have several pension inputs as sometimes a client can have 2 monthly pensions and the spouse may have 1, each may grow at a separate inflation rate if any so we need flexibility here.  In this example there is just the 1 monthly pension of $1,283 and doesn’t inflate. 

Column E = Shortage or surplus.  This is a simple calculation of column A – column C and column D = column E  In this example the expense of $6,820 exceeds the social security and pension expenses by $1,716 so that amount is coming out of the beginning capital. 

Column F and G are one of the same just and example of different rate of return.  This is the more challenging calculation which it is most likely easier for the developer to see the formula because you have the rate of return and you have a monthly shortage working at the same time.  I have a hard time understanding the calculation when I click on the particular cell.  Also, I subtract on 1 time expenses at random times for car purchase, roof etc and sometimes add on lump sums for sale of house or inheritance and random years.

Life Insurance Forcaster (see attachment CNA1.pdf)

Attached is the output for the life insurance or capital needs analysis.  It would be a good one for the developer to look at this file to see the inputs. 

  • The standard age, retirement age, life expectancy age etc carries from the Data tab.
  • If client is working we put in their income.
  • Then we put in the monthly expenses pre retirement if working and post retirement for everyone.
  • Then we put in the expected social security and any pensions that they have, may be several.
  • Input immediate large expenses, funeral, debts etc.
  • Estate settlement costs
  • Group life insurance if they have any.
  • Individual life insurance if they have any.
  • Current liquid assets.
  • Rate of return – we choose
  • Inflation rate – we choose
  • Output shows Capital Needs A and Capital Needs B.  One is for each spouse in the case the other passes away.

Loan Modeler (see attachment Loan.pdf)

This one is straight forward. We enter # payments, interest rate and amount borrowed and it does the rest.  This one is like any other amortization schedule.

I do build other loans from the original loan file. So I have their mortgage as the “Loan File”

Then I copy that file and make one for their car loan or home equity etc.  I just want to point out that I may need multiple loan files.

Education Fund Forecaster (see attachment EDF1.pdf)

This is straight forward too.  Might help to have developer view the inputs.

  • We enter the kids name, age (which I think should be DOB instead), age college begins and cost of college.
  • There are multiple lines for additional kids.
  • Then we enter money already saved, if any.
  • Then we enter inflation rate for college and the rate of return for the capital saved.  Both rates we determine.
  • The program does the rest to figure out how much you would need today to cover the cost or how much to save monthly on a linear line.

Long Term Care Forcaster (see attachment LTC1.pdf)

This one is very similar to the Retirement Forecasters.  Output is pretty close. The difference is showing impact of having a long term care need and whether or not you have coverage to pay for it.

We found a flaw with the logic of the original design of this which I will point out below.

So all the inputs are the same from the Retirement version, until you get to line 34-37.  The developer should look at this.

Here we put in the amount of expense and coverage for the need. 

We put in the age the need begins and ends.  We usually do 3-5 years

Then we enter the inflation protection rate, if any.

So we basically recommend the policy we think they should have which fills in these values.  We would show 6000 month need and coverage with 5% inflation rate.

The we enter the beginning capital and the rate of return for each column, No LTC  (Column F) or with Long Term Care (column G).

Column A is the monthly expense, including the cost of the LTC insurance as an add on that doesn’t inflate.  Similar to a mortgage.

  • Here is the issue in the current logic.  The comparison is showing what happens when you HAVE a long term care need and you either have coverage or you don’t.  It doesn’t factor in if you don’t have the coverage, you don’t have the cost of the premium.  Column A should be less the premium when factoring in column F.
  • Column G shows if you have a long term care need and you have the coverage, how it looks which is accurate because in order to have the coverage you would need to have the expense.  Column A should have a higher cost (ie the premium). So technically, it isn’t a fair comparison as your expense is too high in the not having coverage example.

Column B is monthly savings, until you get down to the age where you have a need for long term care.  This shows the actual benefit coming in to offset the cost rising.  You can see the expense jump up at age 80, column D goes up as no insurance to cover the additional burden, column E doesn’t have a bump as the insurance covers the cost.

Age 83, the cost drops back down as most likely the client in need of the care has passed on and the remaining spouse no longer has that cost or the premium for the coverage.


We would like to segment this project into six milestones, one for each forecasting application and the last milestone for a system that saves client accounts with easy modification of input variables. Please provide (1) your methodology; (2) the technology stack that you would use to develop the system; (3) timeline; and (4) your expertise with this kind of forecasting system development.  We are technology agnostic but would like to ensure that the system is user-friendly and will not be dependent on on our operating system.  We also need to ensure that they system can be easily backed-up so we don't lose client data.

Financial Forecasting
BI Development
Reporting

$7,000 - $15,000

Starts Mar 06, 2015

4 Proposals Status: COMPLETED

Client: S********* ******** ****** ***

Posted: Feb 23, 2015

Report design and automation in IBM Cognos TM1 Perspectives

Objective:

We need to efficiently design and automate reporting packages in our new TM1 Perspectives tool. The goal is to utilize a skilled developer to quickly build automated reports in TM1 based on existing templates, and ad-hoc reports. The developer may need to make coding and data structure enhancements to the existing TM1 tool. (See attached file for example of reporting package)

The tools and data sources we are working with:

·         Business Intelligence System: IBM Cognos TM1 Perspectives

·         Data Warehouse: SQL

·         Data Sources: 4 vendors providing various flat files into FTP server which SQL runs nightly ETL process to download. 

Transportation and Warehousing
Finance
Analytics

$50/hr - $80/hr

5 Proposals Status: CLOSED

Client: W******* ****** *****

Posted: Feb 13, 2015

Stock Price Prediction Using Machine Learning

I am looking for someone with expertise in Machine Learning/Deep Learning who also has extensive knowledge of financial statements and financial data. 

I have pulled data from a database of financial information for every stock in North America from 1979 - present day. I have chosen 35 different features, all of which I know are highly correlated with a stock's return, based on numerous studies and incremental knowledge from the past 60 years. I am hoping that by standing on the shoulders of giants, and adding in a machine learning element through the use of neural networks or other machine learning algorithms, the algorithm will be able to make connections between the different positively correlated features in ways that a person would never be able to find on their own, leading to high returns.

Once the algorithm finishes training, I will want the data scientist to help me filter the training data by stock year with the hope of finding a certain optimal # of stocks to invest in per year that will lead to a combination of a high return with as low of a drawdown/Standard Deviation as possible during the bad years.

Successful work on the project could lead to continued work augmenting the project throughout the year.

While the preferred location says New York, NY, that's definitely not an actual restraint if the right person is outside of NY. If you live in NY, it would just be nice to be able to meet/chat in person is all, but don't let the location preference stop you from applying if you're outside of NY!

Stock Market
Stock Trading
Financial Markets

$5,000 - $12,500

Starts Mar 15, 2015

11 Proposals Status: COMPLETED

Client: G********* ******* ***

Posted: Feb 12, 2015

Marketing Sales Prediction Algorithm using Prior Sales Data

UPDATE 2-12-2015: At current we're in the process of reviewing bids that have already been submitted and not accepting new bids.

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Goals: We'd like to have an algorithm developed that can look at a large data set and identify our potential customers with a high degree of accuracy. The algorithm should also be able to identify non-potential customers with a high degree of accuracy.

This will allow us to lower our marketing costs and/or completely eliminate non-buyers from our marketing pool.

We have two data sets to be building an algorithm from and should be used to test the accuracy of the algorithm against.

Each data set of individuals is about 700,000-800,000 with about 4000 buyers in each.

There is a variety of parameters associated with each individual, from address to birthday, to high school type, to high school name and gender. Also beyond this, we're open to using data enhancement services at your recommendation (which we have available) to include household income, credit and/or any other parameters deemeded testable. The data enhancement service has about 1000 additional parameters which they can attach beyond what we have.

At the end of this, I'd like to have an algorithm I can feed new data into that will identify the most likely buyers based upon the two previous data sets such to tag a new live data set we'll be mailing and see if the algorithm performs in the wild.

Data will be provided in CSV format at project start time.

Education
Media and Advertising
Customer Segmentation

$2,000 - $5,000

Starts Feb 17, 2015

23 Proposals Status: IN PROGRESS

Client: T**** **** *** *** *********

Posted: Feb 02, 2015

Ad Hoc Consultancy on applying Gene Expression Chip analysis algorithms in other fields

Have a conversation to provide input on algorithms employed in DNA microarrays and discuss potential for applications in social science fields.

Pharmaceutical and Life Sciences
Analytics
Microarrays

$100/hr - $150/hr

Starts Jan 29, 2015

12 Proposals Status: CLOSED

Client: S**** **** ********** ****

Posted: Jan 28, 2015

Channel recommendation engine

We have a dataset of cable TV viewers.  For each viewer we have a zip code, a list of channels watched, and average number of hours each channel is watched.  We also have a master list of channels, so that we can see what channels each viewer does not watch.

We are looking to create a channel recommendation engine.  When we get a new record (a new viewer, with their zip code and the average hours they watch each channel) we'd like to recommend which channels, of the channels they do not watch, they would most likely want to watch based on others with similar viewing habits.  The engine should return these recommended channels in descending order of likelihood to watch, with some metric of likelihood to watch.  We can also use the zip code, and demographic info that is publicly available by zip code, as additional predictors to refine the model.

The engine should be created with open source tools (R, Python, Mahout, whatever) and provided as the deliverable for this project.

We will start this project in the first quarter of 2015.

Media and Advertising
Telecommunications
Customer Behavior Analysis

$500 - $2,500

Starts Mar 15, 2015

20 Proposals Status: IN PROGRESS

Client: T********* *******

Posted: Jan 22, 2015

Google Analytics - Factor Analysis & Data Vizualisation

I need help to pull data from Google Analytics API into some other platform (possibly Tableau, Watson, etc.) to: 

1. perform factor analysis of the combinations of factors that are more likely to indicate that a particular group will purchase (we've identified about 15 starting points for this)

2. show this data in a new, clear way

I believe the API part is necessary to pull all the needed data out of GA

The data viz part is a bonus - this is to enable me to present it in a way never seen before (to the people I need to show it to at least!).

The factor analysis is the most urgent part.

Google Analytics
vizualisation
Factor Analysis

$26/hr - $60/hr

Starts Jan 21, 2015

4 Proposals Status: IN PROGRESS

Client: W********

Posted: Jan 19, 2015

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