We're seeking to collaborate with motivated, independent PhD graduates or doctoral students on approximately seven new projects in 2024. If you’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.
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.
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:
- Predictive Modeling with GitHub Logs: Develop models to predict market trends and investment opportunities using GitHub activity and developer data.
- Satallite Data Analysis: Explore non-traditional data sources such as social media sentiment, satellite imagery, or web traffic to enhance financial forecasting.
- Data Imputation Techniques: Investigate new methods for handling missing or incomplete data to improve the robustness and accuracy of our models.
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.
- Innovative Environment: Engage with the latest technologies and methodologies in machine learning and finance.
- Collaborative Team: Work alongside a team of experts passionate about driving innovation in investment insights.
- Flexible Projects: Tailor your research to align with your interests and expertise, with the freedom to explore new ideas.
- Experienced Researchers: Experts previously from NYU, Columbia, Oxford-Man Institute, Alan Turing Institute, and Cambridge.
- Post Research: Connect with alumni that has moved on to DRW, Citadel Securities, Virtu Financial, Akuna Capital, HRT.
If you’re excited about leveraging your expertise in machine learning and finance to drive impactful research and projects, we’d love to hear from you! Please reach out to us at [email protected] 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