Data Scientists

Qualifications:Education:Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.Experience:Exploratory Data Analysis (EDA):Proficiency in performing EDA to understand data characteristics and identify patterns, trends, and anomalies.Experience in data cleaning, data preprocessing, and dealing with missing or inconsistent data.Machine Learning Model Building:Proven experience in developing, training, and validating machine learning models for various applications.Strong understanding of supervised and unsupervised learning algorithms, including regression, classification, clustering, and dimensionality reduction.Experience in time series forecasting, anomaly detection, and natural language processing is a plus.Programming Skills:Proficiency in Python programming, with a deep understanding of data structures, algorithms, and object-oriented programming.Experience with Python-based data science and machine learning libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, Keras, and PyTorch.Experience with SQL for database querying and data manipulation.Feature Engineering:Expertise in creating new features from raw data to improve model performance.Knowledge of feature selection techniques to reduce dimensionality and prevent overfitting.Data Visualization:Ability to create insightful and interactive visualizations to communicate data findings and model results.Proficiency with data visualization tools such as Matplotlib, Seaborn, Plotly, or Tableau.Preferred Experience:Experience with deep learning techniques and frameworks such as TensorFlow and PyTorch.Familiarity with MLOps practices and tools for continuous integration, delivery, and monitoring of machine learning models.Previous experience in industries such as safety, compliance, or engineering is a plus.

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