Position: Data Scientist
Company: Yalantis
Category: Data Science
Experience required: 3y
English level: upper

We are seeking a talented and highly skilled Data Scientist with expertise in Artificial Intelligence (AI), Deep Learning (DL) and Machine Learning (ML). As a member of our dynamic team, you can leverage cutting-edge technologies and advanced algorithms to solve complex data problems. This role is crucial in driving data-driven decision-making and enhancing our organization’s competitive advantage.

Responsibilities:
- Develop and deploy AI and ML models to analyze and interpret large volumes of structured and unstructured data.
- Collaborate with cross-functional teams to identify business challenges and develop data-driven solutions.
- Conduct exploratory data analysis, data preprocessing, and feature engineering to extract meaningful insights from complex datasets.
- Design and implement scalable and efficient machine learning algorithms and models for various applications.
- Stay up-to-date with the latest advancements in AI and ML technologies, frameworks, and libraries.
- Evaluate and validate model performance using appropriate statistical measures and data visualization techniques.
- Communicate complex technical concepts and insights to both technical and non-technical stakeholders.
- Collaborate with software and data engineers to integrate AI/ML models into production systems.

Technology Stack:

- Programming Languages: Python (primary language), R (optional)
- Data Manipulation and Analysis: Pandas, NumPy, SQL
- Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-learn
- Deep Learning Frameworks: Keras, TensorFlow, PyTorch
- Data Visualization: Matplotlib, Seaborn, Plotly
- Big Data Technologies (optional): Apache Spark, Hadoop, Hive
- Version Control: Git
- Cloud Platforms: AWS (primary), Azure, GCP

Typical Algorithms:

- Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, Support Vector Machines (SVM)
- Unsupervised Learning: Clustering (K-means, Hierarchical), Principal Component Analysis (PCA), Anomaly Detection
- Deep Learning: Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (GAN), Transformers
- Natural Language Processing (NLP): Word Embeddings (Word2Vec, GloVe), Named Entity Recognition (NER), Sentiment Analysis, Language Translation
- Recommender Systems: Collaborative Filtering, Content-Based Filtering, Hybrid Methods

Requirements:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
- Solid understanding of statistical concepts and machine learning algorithms.
- Proficiency in Python programming, with experience in developing and deploying ML models using Python libraries.
- Strong knowledge of AI and ML techniques, including deep learning and neural networks.
- Experience in data preprocessing, feature engineering, and data visualization.
- Experience in natural language processing (NLP) and machine learning models for text classification and sentiment analysis
- Experience in implementing and deploying recommendation systems
- Experience in designing and implementing scalable, reliable, and efficient machine learning systems that can handle large-scale data processing
- Familiarity with containerization technologies, such as Docker and Kubernetes, and cloud computing platforms, such as AWS, Azure, and Google Cloud Platform
- Experience with model versioning, testing, and monitoring, including automated testing, continuous integration, and continuous deployment (CI/CD) practices
- Understanding of ML Life Cycle (MLOps): Scoping, Data, Modeling, Deployment
- Familiarity with big data technologies.
- Excellent problem-solving and analytical skills.
- Strong communication and teamwork abilities.
- Intermediate Strong English or higher

Our benefits
- Great compensation and social packages;
- Medical insurance;
- Education compensation;
- Opportunities for professional growth and support for skills development;
- Full reimbursement of certification (including AWS);
- Workation and relocation program (Larnaca, Warsaw)
- Financial and legal support for private entrepreneurs
- Knowledge-sharing atmosphere;
- Team building and corporate activities;
- Special corporate currency and merch store