# Data Scientist

**Mode of work:** Full time, remote, flexible hours\
**Location:** preferably GMT+2 to GMT+8\
**Work experience:** 3+ years

Synnax is looking for a Data Scientist to join our fully remote, distributed team of amazing engineers to help shape the future of Synnax and future of fintech. We are looking for someone who is passionate about data science and machine learning, has autonomy and initiative, and is able to formulate hypotheses and critically test them with data; can source their own data and detect a signal in pure noise; can turn vague ideas into data-driven decisions.

### <sub>About Us</sub>

Synnax is pioneering the future of credit ratings with AI-powered credit intelligence. Our platform leverages a decentralized, bias-resistant consensus mechanism to aggregate machine learning model predictions, delivering robust, forward-looking credit insights for both public and private companies. By integrating decentralized AI, privacy-preserving computation, and blockchain technology, we provide real-time, unbiased, and predictive financial metrics that go far beyond traditional credit ratings. Synnax empowers companies to showcase their creditworthiness securely, access new sources of credit, and benefit from transparent, data-driven evaluations—all while maintaining full control over their data privacy. Headquartered in Dubai, we are redefining credit analysis for the digital asset and conventional credit markets.

### <sub>Key Responsibilities</sub>

* Building predictive models (classification/regression) bases on large volumes of financial, blockchain and macroeconomical data.
* Apply both traditional machine learning and modern LLM (Large Language Model) frameworks and APIs to extract insights from data.
* Write documented and maintainable code for production environment.
* Communicate findings and recommendations clearly to both technical and non-technical stakeholders.
* Stay up-to-date with the latest developments in data science, machine learning, and AI.

### <sub>Required Skills & Qualifications</sub>

* **Education:** Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
* **Language:** Applicant must have a solid English language knowledge: written & spoken.
* **Experience:** 3+ years of professional experience in a data science or machine learning role.
* **Technical Skills:**
  * Proficiency in Python, with strong knowledge of data science libraries (e.g., pandas, scikit-learn, NumPy, TensorFlow, PyTorch, transformers).
  * Experience with data preprocessing, feature engineering, and model evaluation.
  * Hands-on experience with modern LLM frameworks and APIs (e.g., OpenAI, Hugging Face, LangChain).
  * Strong knowledge of traditional machine learning algorithms (classification, regression, etc.).
  * Experience with data visualization tools (e.g., Matplotlib, Seaborn, Plotly).
  * Experience building ML APIs (Flask, FastAPI, etc.)
* **Soft Skills:**
  * Excellent problem-solving and analytical skills.
  * Strong communication and collaboration abilities.

### <sub>Nice-to-Have</sub>

* Exposure to financial datasets and/or blockchain data analysis.
* Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools.
* Software engineering skills (e.g., version control, containerization, CI/CD) are a plus.
* Familiarity with data engineering concepts and tools (e.g., Airflow, Spark).

### <sub>What We Offer</sub>

* Competitive salary
* Flexible working hours and remote work options
* Opportunity to work with cutting-edge technologies and innovative projects
* Supportive, collaborative, and inclusive work environment
* Professional development and learning opportunities

### <sub>How to Apply</sub>

If you are ready to take your data science career to the next level, please submit to <danil@synnax.ai> your resume and a brief cover letter outlining your relevant experience and why you would be a great fit for our team.

**Apply now and join us in shaping the future with data!**

Synnax is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.


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