Data Scientist
Work mode: contract, fully remote
Description: 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:
- Develop and implement advanced machine learning models and statistical algorithms to solve business problems and improve decision-making.
- Perform exploratory data analysis to identify trends, patterns, and opportunities within large datasets.
- Collaborate with stakeholders to understand business objectives and translate them into data-driven solutions.
- Developing processes and tools to cross-validate data.
- Database management (create automated tools for data structuring, including data cleansing and validation)
- Development of algorithms for natural language processing
- Testing and improving existing algorithms
- Developing custom data models and forecasting algorithms and their validation.
- Working with advanced data visualization tools, including Chat-GPT Code Interpreter, Power BI, and in-house development tools.
- Work closely with other teams to monitor the quality of models implementation for commercial use.
- Documentation and reports preparation for clients and management.
- Excellent organizational and time management skills, with the ability to prioritize tasks effectively.
- Implement data preparation and feature engineering pipelines for the models
- Plan and implement algorithms for predictive modeling.
- Provide continuous improvement of models in production
Qualifications:
- Master or higher degree in Physics, Mathematics, Statistics, Quantitative Finance, Computer Science, or another quantitative field.
- Strong problem-solving skills with an emphasis on research product development.
- Experience working with and creating data architectures.
- Experience with a variety of machine learning and deep learning techniques and understanding of their limitations.
- Advanced knowledge of Python (SciPy, NumPy, Pandas, TensorFlow), and 1 year of experience in advanced NLP algorithms is a huge plus.
- Good written and verbal English.
- Desire to know more about new technologies and research prospective markets.
Why Join Us?
We value knowledge above profit. Our projects aim to push the boundaries of technology and achieve meaningful change. If you are tired of conventional roles that lack ambition and impact, and if you seek to contribute to something greater, join us in redefining the future of technology for the betterment of humanity.
In joining us, you will embark on a journey of fast-paced growth that demands focus and dedication. You will be tasked with solving complex and unprecedented data science problems, working at the cutting edge of your technical domains, and finding creative solutions in an international environment alongside equally exceptional and talented peers. This position provides ongoing opportunities to challenge yourself, making it ideal for the most promising individuals eager to thrive in a dynamic and intellectually stimulating setting.
Required languages
English | B2 - Upper Intermediate |