Data Scientist @ Sindhiya P Hiring

Job Description

Job Title: Data Scientist with Anaconda

Responsibilities:

Data Analysis: Conduct exploratory data analysis (EDA) using Anaconda tools such as Jupyter Notebook, pandas, NumPy, and matplotlib to gain insights from various datasets.
Machine Learning: Develop and deploy machine learning models using Anaconda's machine learning libraries such as scikit-learn, TensorFlow, and PyTorch. This involves tasks such as data preprocessing, model training, evaluation, and hyperparameter tuning.
Statistical Analysis: Apply statistical methods and techniques to analyze data and extract meaningful patterns and trends. Utilize Anaconda's statistical libraries such as SciPy and stats models for hypothesis testing, regression analysis, and more.
Data Visualization: Create informative and visually appealing data visualizations using tools like matplotlib, seaborn, and Plotly within the Anaconda ecosystem to communicate findings effectively to stakeholders.
Collaboration and Documentation: Work closely with cross-functional teams including data engineers, software developers, and business analysts to understand requirements, develop solutions, and communicate results. Document analysis methodologies, findings, and recommendations for future reference.
Workflow Optimization: Continuously seek opportunities to optimize data science workflows using Anaconda's integrated environment. Identify and implement best practices for code efficiency, reproducibility, and scalability.
Stay Current with Industry Trends: Keep abreast of the latest developments in data science, machine learning, and related fields. Stay updated on new features and enhancements within the Anaconda ecosystem and evaluate their potential impact on existing workflows.

Experience with data manipulation, cleaning, and preprocessing using tools like pandas and NumPy.
Excellent analytical and problem-solving skills, with the ability to translate business requirements into actionable insights.
Strong communication and interpersonal skills, with the ability to effectively collaborate with multidisciplinary teams.
Familiarity with version control systems (e.g., Git) and experience working in a Linux environment is desirable.
Prior experience with Anaconda distribution and its associated tools is mandatory.

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Keyskills:   artificial intelligence data science machine learning data anaconda scientist