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Python Business Analytics


๐ŸŒŸ We Are Growing!

We're seeking to collaborate with motivated, independent PhD graduates or doctoral students on approximately seven new projects in 2024. If youโ€™re interested in contributing to cutting-edge investment insights and data analysis, please get in touch! This could be in colaboration with a university or as independent study.

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๐Ÿš€ About Sov.ai

Sov.ai is at the forefront of integrating advanced machine learning techniques with financial data analysis to revolutionize investment strategies. We are working with three of the top 10 quantitative hedge funds, and with many mid-sized and boutique firms.

Our platform leverages diverse data sources and innovative algorithms to deliver actionable insights that drive smarter investment decisions.

By joining Sov.ai, you'll be part of a dynamic research team dedicated to pushing the boundaries of what's possible in finance through technology. Before expressing your interest, please be aware that the research will be predominantly challenging and experimental in nature.

๐Ÿ” Research and Project Opportunities

We offer a wide range of projects that cater to various interests and expertise within machine learning and finance. Some of the exciting recent projects include:

Please visit docs.sov.ai for more information on public projects that have made it into the subscription product. If you already have a corporate sponsor, we are also happy to work with them.

๐ŸŒ Why Join Sov.ai?

๐Ÿค How to Apply

If youโ€™re excited about leveraging your expertise in machine learning and finance to drive impactful research and projects, weโ€™d love to hear from you! Please reach out to us at research@sov.ai with your resume and a brief description of your research interests.

Join us in shaping the future of investment insights and making a meaningful impact in the world of finance!

A series looking at implementing python solutions to solve practical business problems. Share your own projects on this subreddit, r/datascienceproject. Every week we will look at hand picked businenss solutions. See the following google drive for all the code and github for all the data. If you follow the LinkedIn page, you would be able to see the lastest developments.


All projects are of intermediate to advanced difficulty and the projects are not presented in any particular order; nothing stops you from starting at week six for example.

Week 1/52: Bike Share Business Case - Google Colab

Outlier Analysis, Model Selection, Missing Values, Descriptive Statistics

Week 2/52: Reuters Author NLP - Google Colab

Process Text, pyLDAvis, Word Embeddings, Text Evaluation, fuzzywuzzy

Week 3/52: Customer Lifetime Value - Google Colab

RFM Analysis, Pareto Model, NDB Model, Gamma-Gamma Model, CLV Model, Constraint Programming

Week 4/52: Customer Segmentation - Google Colab

Radar, Silhouette, PCA, Grouping, Invoices, Inventory, Datatable, Basket,

Week 5/52: Customer Visits - Google Colab

Week, EDA, Simulated, Prediction, Dummy Variable

Week 6/52: Demand Forecasting - Google Colab

Neural Network, Sales, Relu, LSTM, CNN, Evaluation

Week 7/52: AirBnB Sydney Rent Evaluation - Google Colab

Full Pipeline, Random Forest, Visualisation, Grid Search, Confidence Interval

Week 8/52: Portfolio Optimisation - Google Colab

Efficient Frontier, Stocks, Modern Portfolio Theory, Pivot, Simulations, Minimum Volatility, Sharpe Ratio

Week 9/52: Economic Analysis - Google Colab

GDP, Life Satisfaction, Linear Regression Plots, Prediction Model

Week 10/52: Loan Classification - Google Colab

Default, Credit Scores, Visualisations, Data Cleaning, ROC Curves, Multi-class Classification

Week 11/52: Venture Capital - Google Colab

Capital Allocation, Decision Trees, Acquisitions, Investment

Week 12/52: Bankruptcy Prediction - Google Colab

Voting Classifiers, Bagging Ensembles, SMOTE, XGBoost, Cross-validation

Week 13/52: HR Analytics - Google Colab

OSEMN, Bagging Ensembles, AUC, Model Comparison, ROC Graph, Feature Importance Graph