8 Capgemini Data Scientist Jobs

Data Scientist

Exp : 6-14 Years

I. Proficiency in programming languages like Python

II. Skills in handling and analysing large datasets, including data cleaning, wrangling, transformation, and exploratory data analysis (EDA) using tools like pandas.

III. Knowledge of statistical concepts such as hypothesis testing, regression analysis, ANOVA, experimental design, and probability theory.

IV. Understanding machine learning algorithms, supervised and unsupervised learning, feature engineering, model selection and evaluation, and hyperparameter tuning is essential, with libraries like scikit-learn, TensorFlow, or PyTorch commonly used. Knowledge of YOLO is desirable

V. Data visualisation skills using libraries like Matplotlib, Seaborn, or ggplot

VI. Familiarity with big data technologies like Apache Hadoop, Apache Spark, or distributed databases enables the processing and analysis of large-scale datasets.

VII. Proficiency in SQL and database management

VIII. Knowledge of data engineering concepts, including data pipelines, integration, warehousing, and architecture, is beneficial.

IX. Cloud computing platforms (Azure) and services like Azure Machine Learning can be advantageous.

X. Proficiency in version control systems like Git is crucial for effective collaboration and code management.