Job Location: Bengaluru
– Bachelor’s or Master’s degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience.
– Good programming skills in Python Strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc.
– Experience applying various machine learning techniques and understanding the key parameters that affect their performance.
– Experience developing experimental and analytic plans for data modeling processes, use of strong baselines, and the ability to accurately determine cause and effect relationships.
– Have a history of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs.
– Understanding of relevant statistical measures such as confidence intervals, the significance of error measurements, development, and evaluation data sets, etc.-
– Experienced in using multiple data science methodologies to solve complex business problems.
– Experienced in handling large data sets using SQL and databases in a business environment.
– Excellent verbal and written communication. Strong troubleshooting and problem-solving skills.
– Thrive in a fast-paced, innovative environment.
Location : Bangalore, Karnataka, India
– Data Science, Deep learning, ML/Model
– Imoka – SQL, Python – 30min online test
– Look people only from Data Science Background
– If people are from Retail background it’s an added advantage
– Requirement is open for Both SBA & AC
Senior Data Scientist Responsibilities :
– Formulating, suggesting, and managing data-driven projects which are geared at furthering the business’s interests.
– Collating and cleaning data from various entities for later use by junior data scientists.
– Delegating tasks to Junior Data Scientists in order to realize the successful completion of projects.
– Monitoring the performance of Junior Data Scientists and providing them with practical guidance, as needed.
– Selecting and employing advanced statistical procedures to obtain actionable insights.
– Cross-validating models to ensure their generalizability.
– Producing and disseminating non-technical reports that detail the successes and limitations of each project.
– Suggesting ways in which insights obtained might be used to inform business strategies.
– Staying informed about developments in Data Science and adjacent fields to ensure that outputs are always relevant.
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