Remote Senior Data Scientist

Summary

Join OmniData as a Senior Data Scientist to synthesize and leverage business data, enhance capabilities for overall goal achievement, and build value-driven solutions. This role supports stakeholders through quantitative analytics and advanced analytics for key initiatives.

Responsibilities

• Build Data Science solutions from beginning to end by devising and utilizing algorithms and models to mine big-data stores
• Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, design simulations and experiments, developing statistical and ML models by tailoring to business needs, and collaborating with Data Scientists, Data Engineers, BIE's, and Product Managers
• Deliver with independence on challenging large-scale problems with complexity and ambiguity
• Write code (Python, R, Scala, SQL, etc.) to obtain, manipulate, and analyze data
• Improve data-driven decision-making through rigorous statistical analysis and clear communication with stakeholders
• Build Machine Learning and statistical models to solve specific business problems
• Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance
• Analyze historical data to identify trends and support optimal decision making
• Apply statistical and machine learning knowledge to specific business problems and data
• Formalize assumptions about how our ML systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed
• Build decision-making models and propose effective solutions for the business problems you define
• Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication
• Implement analytical models in production by collaborating with software developers, data engineers and ML-engineers
• Design, develop, and implement data management systems of analytic frameworks for the business’s data
• Apply advanced statistical capabilities and deliver statistical models, for example, consumer predictive value, churn, segmentation and profiling, association models, and so forth
• Refine and draw reports and presentation on junior data science departmental performance as well as proposed data science and analytics strategies
• Formulate new and creative ideas for leveraging the business’s vast collection of data in the databases
• Develop and implement state-of-the-art analytical algorithms for object detection, segmentation, classification, and recognition
• Model complex discovering insights and identifying business opportunities using algorithmic, statistical, visualization, and mining techniques
• Translate business requirements into quick prototypes and enable the development of big data capabilities, frameworks, and governance processes in the department and the business at large enabling more effective execution of data and analytics campaigns and the achievement of overall business targets/objectives
• Work closely with junior data scientists in developing new and improved machine learning systems, all the way from prototyping to production
• Work with senior management and key stakeholders in identifying and prioritizing actionable, impactful insights across a variety of core business fronts, driving informed decision-making across the business and, hence, enhancing the business’s capability to achieve goals and objectives
• Keep up and provide insights to the data science department and the larger Data and Analytics department on leading data science and analytic practices, trends, design, learning and development cycles, which improves the business’s overall performance by improving data and analytics programs that provide high-impact insights
• Perform similar duties as he deems fit for the proper execution of his duties and duties as delegated by the MD/HoD