Company Name:-
Tredence

Job Location:-
Bengaluru, Karnataka

Job Summary:-
JOB DESCRIPTION
Roles & Responsibility:
Possesses strong analytical/logical thinking and communication skills
Collaborate with the data warehousing team, ensuring that data infrastructure supports the needs of our analytics team and validating data quality
Coordinate with business planners and decision makers to translate business questions into verifiable hypothesis and data models
Develop clear, concise, actionable models and recommendations from mountains of data
Advocate for exploration of interesting data anomalies or patterns that may provide more explanatory detail about customer behaviours or predictive value to the business
Partner closely with business and technical teams to understand their project objectives and provide data-driven solutions and recommendations
Design and develop data preparation components and processes that extract and transform data across disparate databases for reporting and analytics, ensuring integrity of analysis data by developing the requirement specifications and assisting the development and testing of data tables
Ensures solutions are scalable, repeatable, efficient and effective
Work hands-on on various analytics problems and provide thought leadership on problems that we are working on
Interact with onsite team as well as client on daily/weekly basis to gather requirements/provide updates
Be involved in the development of the company through pre-sales/operational support
Qualifications:
2.

5 to 4 years of experience in applying advanced algorithms on complex and large data sets and in data insights
Experience into Statistics, Programming and Machine Learnig skills, knowledge of Modelling (Predictive, Time Series etc.

)
Highly proficient in applying Machine Learning and Deep Learning techniques on Python
Exposure to Power BI and Azure Databricks is an advantage
Proven ability to dig-in and understand the data and to leverage creative thinking and problem-solving skills in solving open ended business problems
Fair understanding of data infrastructure, data warehouse, or data engineering
Coordinate with business planners and decision makers to translate business questions into verifiable data models and hypothesis
Work with engineers to operationalize and monitor statistic

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