Data Scientist (DL, Neural Networks)

Position Overview

We are seeking an experienced Data Scientist specializing in neural networks. The ideal candidate will have 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:

  • Develop and implement bespoke data science solutions and machine learning models.
  • Plan and implement algorithms for predictive modeling.
  • Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers, data analysts, and DevOps specialists.
  • Provide expertise in tuning loss functions, metrics, sample weights adjustment.
  • Contribute to resolving clients' business problems using data science tools and algorithms.

 

 

Required Skills and Qualifications:

  • Minimum of 2 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 nto accept candidates with partial experience in python, as our projects require solid 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 productionizing models for real-time data streams.
  • 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.
  • 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.
     

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

  • Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
  • Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
  • Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
  • Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
     
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