Data Scientist  

Data scientists are expected to be statistically minded, with experience in programming and building analytic models. They develop algorithms and utilize analytic platforms in order to answer complex questions, and make sense with data.

• Analyze, interpret data, and communicate results to clients.
• Data exploration, mathematical/statistical modeling, data analysis, and hypothesis testing.
• Design, development, and deployment of Predictive models and frameworks.
• Explain complex mathematical/statistical concepts to clients and advice on strategy.
• Well-versed in quantitative analysis, research, data mining, trend analysis, customer profiling, clustering, segmentation and predictive modeling.
• Collaborate with other members of the team to provide business solutions the client.

We are looking for individual with the mindset of Curious data wizard with below details:

• Master’s or PhD degree in computer science, statistics, mathematics, analytics, data science, informatics, artificial intelligence, visualization, information retrieval or related fields;

• NOTE: Bachelor graduate with a high GPA score will be considered

• Experience with modeling techniques such as clustering, linear & logistic regression, random forest etc.
• Must have a passion for data.
• Experience in data mining and data analysis.
• Excellent in critical thinking, analytically, creatively, critically and inquisitively.
• Ability to work in a proactive, highly engaging, client oriented environment.
• Good understanding of common statistics, data mining & machine learning methodologies & models;
• Knowledge of human-computer interactions, visualization and knowledge representation;
• Background in software engineering
• Experience working with large datasets, and mixed data types and sources in a networked and distributed environment;
• Experience in data extraction and processing, feature engineering and correlation analysis;
• Substantial experience with state-of-the-art analytics-oriented scripting, data structures, programming languages, and development platforms in a Linux, cloud or distributed environment;
• Theoretical background and domain knowledge for the evaluation of the technical and business merits of analytic findings;
• Excellent written and verbal communication and organizational skills, ability to write and edit analytical materials and reports for different audiences, and capacity to transform analytical concepts and outcomes into business-friendly interpretations; ability to communicate actionable insights to non-technical audiences, and experience in data-driven decision making.