We are looking for a motivated financial data scientist to join our Quantitative Research team. The ideal candidate will possess a strong foundation in programming and machine learning, a passion for finance, and a basic understanding of financial principles.
Key Responsibilities
Explore, analyze, and implement state-of-the-art research papers on machine learning methodologies for financial time-series forecasting and portfolio optimization.
Design and develop backtest for ML strategies to assess their performance and robustness.
Develop interactive dashboards to monitor and analyze performance evaluation criteria for developed strategies.
Continuously stay updated on advancements in machine learning and quantitative finance.
Optimize strategies for real-world implementation.
Qualifications
Educational Background
Bachelor’s or Master’s a quantitative field such as Computer Science, Machine Learning, Statistics, Mathematics, Physics, Engineering, or financial fields such as Finance or Economics.
2. Technical Expertise
Strong programming skills in Python,
Proficiency in machine learning libraries such as PyTorch, scikit-learn, etc.
Experience with data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib or plotly).
Familiarity with OOP principles and implementation.
Experience in designing and implementing modular, reusable, and maintainable codebases.
Familiarity with SQL and/or NoSQL databases (is a plus).
Proficiency in using Git for version control and collaborative coding.
Knowledge of DevOps tools like Docker, Kubernetes, or similar is a plus
Hands-on experience with backtesting frameworks such as Backtrader or zipline is a plus.
3. Experience in Machine Learning
Proven experience in developing and deploying machine learning models (e.g., supervised and unsupervised learning, neural networks, deep learning and reinforcement learning is a plus).
Knowledge of feature engineering, hyperparameter tuning, and model evaluation techniques.
4. Quantitative and Financial Knowledge
Basic foundation in linear algebra, statistics.
Ability to interpret mathematical models and apply them to practical trading strategies.
Knowledge of financial markets (e.g., equities, derivatives, fixed income) and modern portfolio theory.
Familiarity with backtesting, and strategy evaluation.
5. Problem-Solving and Research Skills
Strong ability to identify, analyze, and solve challenging problems independently.
Enthusiasm for learning and staying updated with the latest trends in machine learning and finance.
job benefits:
Loans
Health insurance
Game room
Snacks
Breakfast
Lunch
medical-in-house
Occasional packages and gifts
Learning stipends
Resting space
معرفی شرکت
کارگزاری آگاه، ارائهدهنده خدمات کارگزاری بورس اوراق بهادار، کالا و انرژی تو سال ۱۳۸۴ توسط آقای بهروز ابراهیمی بنیان گذاشته شده و با همراهی افراد جوان، توانمند و باانگیزه به جایگاه خوبی در بین کارگزاریهای ایران دست پیدا کرده.
آگاه سرزمینی برای قصهپردازیست. قصه جستجو، تلاش، امید، اعتماد و تعالی. قصه آدمهایی که دریادل و دوراندیش و متواضعاند، رویا میسازند و برای رسیدن به آن برنامهریزی میکنند، هر لحظه را فرصتی نیکو میشمارند و میدانند که «سختترین طوفان مهمان دریاست نه صاحبخانه آن.» اگر علاقهمند به نقشآفرینی در این قصههای ماجراجویانهاید، ما صمیمانه مشتاق شنیدن دانستهها، تجربهها و آرزوهایتان هستیم.