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The Amazing Way Zomato Uses Data Science For Success

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Presently, the 150-strong engineering team at Zomato includes data scientists, product managers and analysts. "At an individual level, I continue to be fairly hands-on working directly with data which takes 40% part of my time. Another 30% of the time is spent in meetings with team members – clearing roadblocks, ensuring alignment between data scientists/statisticians and ML engineers/developers who are putting models in production," he shared. Another 20% of Mehta's time goes in meeting stakeholders from other teams – since the work directly impacts different business verticals and product features, so alignment with business heads and product managers is critical. "The rest 10% is dedicated to learning and developing – data science domain is evolving very fast, and it is crucial to stay abreast of recent developments.


Product Manager - Data Science & Machine Learning

@machinelearnbot

The Data Science and Machine Learning team at Datadog provides mission-critical algorithmic alerting & issue discovery functionality across our Infrastructure, APM and Logs products. Anomaly Detection and Outlier Detection are just the start and we need your help to drive the vision for algorithmic monitoring at Datadog. You will lead new products that utilize trillions of data points across thousands of customers. If you are passionate about Data Science and are excited to work on a fast-moving team in a high-growth environment, we want to meet you!


Do or die – asset managers take up data science - Risk.net

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In the time it takes the Earth to rotate about its axis, internet users will generate 2.5 quintillion bytes of new data. That number, a calculation by IBM, is mostly a slag heap of digital dross. But it's a mountain asset managers can no longer afford to ignore. Whether to spin alpha or just survive, asset managers need to separate the meaningful and profitable from the futile and worthless. "Data science, big data and machine-learning are all becoming


How HR Managers Use Data Science to Manage Talent for Their Companies

@machinelearnbot

Talent acquisition may sound a minuscule term to most of us who have never been on the other side of the table. But in reality, the entire process of hiring is way too time-consuming, expensive and employs a number of resources. Hiring managers are responsible for all the hiring processes taking place in an organization. They have to devise such plans that attract a large number of eligible candidates while creating an environment where candidates would prefer to stay. A solution to simplify the task of staffing is through the use of data effectively according to the needs and requirements.


Data Scientist – Consultant, Manager, Senior Manager (Consulting) – London UK Wide Travel

#artificialintelligence

MBN Solutions have been engaged by a world renowned Fortune 500 Consulting client operating across Europe, North America, Asia and the Middle East, to recruit an ambitious and creative (Senior) Data Scientist to help develop and lead on a range of Big Data, Data Science and Advanced Analytical projects.