Description: Deep Knowledge Group is a data-driven consortium of commercial and non-profit organizations active on many fronts in the realm of DeepTech and Frontier Technologies (AI, Longevity, BioTech, Pharma, FinTech, GovTech, SpaceTech, FemTech, Data Science, InvestTech), ranging from scientific research to investment, entrepreneurship, analytics, consulting, media, philanthropy and more.

We are seeking bold, bright ambitious, and experienced data scientists hungry for real challenges and complex project goals to work on data aggregation and cross-validation tasks (with a focus on advanced natural language processing), data management, and advanced data visualization skills.

The ideal candidate will have a strong background in data science, machine learning, and statistical analysis, and will play a crucial role in leading data-driven initiatives across the organization. As a Data Scientist, you will be responsible for designing, implementing, and optimizing data models, and providing actionable insights to inform business decisions. You will collaborate closely with cross-functional teams to solve complex problems and drive innovation through data.

Responsibilities: 

1. Lead the end-to-end development of data science projects, from data exploration and preprocessing to model development, deployment, and monitoring.
2. Develop and implement advanced machine learning models and statistical algorithms to solve business problems and improve decision-making.
3. Perform exploratory data analysis to identify trends, patterns, and opportunities within large datasets.
4. Collaborate with stakeholders to understand business objectives and translate them into data-driven solutions.
5. Mentor and guide junior data scientists and data analysts, fostering a culture of continuous learning and innovation.
6. Developing processes and tools to cross-validate data.
7. Database management (create automated tools for data structuring, including data cleansing and validation)
8. Development of algorithms for natural language processing
9. Testing and improving existing algorithms
10. Developing custom data models and forecasting algorithms and their validation.
11. Working with advanced data visualization tools, including Chat-GPT Code Interpreter, Power BI, and in-house development tools.
12. Work closely with other teams to monitor the quality of models implementation for commercial use.
13. Documentation and reports preparation for clients and management.
14. Excellent organizational and time management skills, with the ability to prioritize tasks effectively.
15. Implement data preparation and feature engineering pipelines for the models
16. Plan and implement algorithms for predictive modeling.
17. Provide continuous improvement of models in production

Qualifications:

1. Master or higher degree in Physics, Mathematics, Statistics, Quantitative Finance, Computer Science, or another quantitative field.
2. Strong problem-solving skills with an emphasis on research product development.
3. Experience working with and creating data architectures.
4. Experience with a variety of machine learning and deep learning techniques and understanding of their limitations.
5. Advanced knowledge of Python (SciPy, NumPy, Pandas, TensorFlow), and 1 year of experience in advanced NLP algorithms is a huge plus.
6. Good written and verbal English for coordinating across teams and reports preparation.
7. Desire to know more about new technologies and research prospective markets.