Data Scientist - Gurgaon, India - WhizHack Technologies Pvt. Ltd.

Description

• Experienced Data Scientist who possesses a passion for designing and driving data science projects forward Have the ability to adapt to rapid changes in test priorities.
• Adjustment of the models and algorithms to improve the accuracy of the result.
• Sharing technical expertise with the team bringing new practices and techniques.
• Break down large or complex data science projects into meaningful subprojects.

• At least 2year deep and handson experience in data science ecosystem (e.g., Python, Spark, Neural Networks/Deep Learning, NLP models, etc.
• Machine learning techniques: Decision Trees, Neural Networks, Deep Learning,
• Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction/engineering, Anomaly deduction
• Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modelling, Time Series, DoE, distribution/probability theory.
• Experience with data visualization tools and spatial analytics.
• Preference to be given for Experience in AWS Cloud Environments
• Experience on SQL/ No SQL database will be added advantages.
• Knowledge of network analysis fundamentals and robust troubleshooting skills
• Experience with Agile and DevOps model, as well as understanding of server scripting and modern deployment and configuration management techniques and tools (Ansible, Ops Works, etc.)
• Ability to write technical documentation, especially in relation to Cloud architecture

• Bachelor's degree or equivalent experience in Computer Science with 13 years of industry experience.
• Strong verbal and written communication
• Proficiency in documentations.

• Flexible schedule
• Food provided
• Health insurance
• Provident Fund
• Work from home

• Monday to Friday
• Morning shift

• Quarterly bonus

• Gurgaon, Haryana: Reliably commute or planning to relocate before starting work (required)