Position: Middle Data Engineer (AWS experience)
Company: Symphony Solutions
Category: Python
Experience required: 2y
English level: intermediate

Project description:
One of the projects is aiming at the creation of valuable insights and forecasts for stock market investors and traders based on companies fundamentals, contracts data, news feed sentiment. It requires strong expertise in neural networks, NLP, and various ML algorithms.
Others include recommendation engines for e-commerce companies as well as for public/private educational organizations.
These projects either startups started from scratch either bring completely new techniques to the mature businesses.

Job Requirements
·       Bachelor or Specialist/Masters in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
·       2+ years of experience in Machine Learning/Data Science applications (classical and deep learning models, ensemble learning)
·       2+ years of experience in Python ML frameworks (NumPy, SciPy, scikit_learn, Pandas, Jupyter, Matplotlib).

Responsibilities:
·        Select and justify the appropriate ML approach for a given business problem
·       Design and implement scalable, cost-optimized, reliable, and secure ML solutions
·       The ability to express the intuition behind basic ML algorithms
·       Create data repositories for machine learning
·       Identify and implement a data-ingestion solution
·       Identify and implement a data-transformation solution
·       Sanitize and prepare data for modeling
·       Perform feature engineering (missing and unbalanced data, outliers)
·       Analyze and visualize data for machine learning
·       Train machine learning models
·       Perform model tuning (learning rate, regularization techniques), hyperparameter optimization
·       Evaluate machine learning models
·       Deploy and operationalize machine learning solutions

Would be a plus:
·       Knowledge of ANSI SQL (ability to write advanced analytical queries)
·       In-depth knowledge in one or more Machine Learning areas: Deep Learning, NLP, Recommender Systems, Reinforcement Learning
·       In-depth knowledge of Tensorflow/Keras
·       In-depth knowledge of AWS SageMaker and one or more of the following related algorithms: Linear Learner, XGBoost, Seq2Seq, DeepAR, BlazingText, Object2Vec, Object Detection, Image Classification, Semantic Segmentation, Random Cut Forest, Neural Topic Model, Latent Dirichlet Allocation, K-Nearest-Neighbors, K-Means, Principal Component Analysis, Factorization Machines, IP Insights, Reinforcement Learning, Automated Model Tuning
·       In-depth knowledge of one or more of the following AWS technologies: S3, Glue, RDS, Aurora, Athena, EMR, SageMaker, Ground Truth, Comprehend, Translate, Transcribe, Polly, Rekognition, Forecast, Lex, Personalize, Textract
·       Hands-on experience with Apache Spark MLLib (Zeppelin)
·       Hands-on experience with OpenCV
Hands-on experience with advanced Python data frameworks (Seaborn, PyTorch, Dask)