We are looking for a Data Scientist to join our client's team. This position is involved in applying data mining methods, using various data tools, building and implementing models, using/creating algorithms, and creating/running simulations with company data.
Processing, cleaning and verifying the integrity of data used for analysis. Solving business problems and building models. Using data visualization techniques is very important for this position. Also within the position to select features, create and optimize classifiers using Machine Learning techniques. Formulate and manage multifaceted analytical studies that are directed against large volumes of data. It is necessary to interpret and analyze data using exploratory mathematics and statistical techniques based on the scientific method. We offer the opportunity to work in a collaborative and inclusive environment with people who value their work and welcome new ideas.
Requirements
• Strong problem-solving, analysis and research skills (experienced in literature research).
• Understanding algorithm analysis, data structures and software design.
• Distributions, statistical tests, regression etc. Deep knowledge of statistics skills such as
• Knowledge of predictive models (such as Naive Bayes, Decision Trees, Tree. Ensembles, SVM, Neural Networks) and optimization techniques.
• Ability to write robust code in Python, Scala or R.
• Numpy, Pandas, Matplotlib, Seaborn etc. Experience with Scientific Python Libraries like Scikit-Learn, Tensorflow, and PyTorch (or equivalents in other languages) with common Python data science frameworks.
• Experience using SQL to manipulate data and gain insights from large datasets
• Good presentation skills with ability to explain sophisticated solution.
• Preferably more than 2 years of Data Scientist experience.
• Having knowledge of SQL, NoSQL databases.
• To have knowledge about Python, R, Java.
Nice to Have
• Excellent communication skills and strong collaboration skills, both oral and written (English).
• Experience in building and using models on cloud platforms (such as AWS, Google Cloud)