We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!
Key Responsibilities: * Create statistical summaries to support hypothesis testing and data-driven decisions during EDA * Implement data preparation and feature engineering pipelines for the models * Plan and implement algorithms for predictive modeling. * Provide continuous improvement of models in production * Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/ * Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists. * Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general. * Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders. * Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.
Required Skills and Qualifications: * Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer. * Proficient in building custom neural networks using PyTorch. * Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling * Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax). * Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus. * Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures. * In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries * Solid understanding of statistics and data analysis. * Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting. * Experience with hyperparameter optimization using libraries like Optuna or Hyperopt. * Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps. * Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting. * Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared. * Familiarity with backtesting functionalities for validating model performance. * Experience in model deployment, including serialization and deployment of models for real-time services. * Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly. * Proficiency in using Git for version control and collaboration. * Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds. * Certifications in deep learning are preferred. * Excellent command of spoken and written English. * Strong self-management, time management, and organizational skills. * Ability to work under a structured management system while independently handling creative tasks. *
What We Offer: * Competitive remuneration package. * Bonuses * Professional mentorship and guidance from experienced team members. * Opportunities for professional growth and continuous learning. * A dynamic and collaborative work environment.
