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Helping CPG companies stay ahead of food trends.

Research Scientist (Head of Data Science)

₹25L – ₹40L • 0.5% – 1.0%
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We are looking for an ambitious researcher to head our R&D efforts to develop one of a kind technologies in the food tech industry using the fundamentals of science (chemistry, biology), general AI, machine learning, and psychology.

dishq is on a mission to build a 'food brain', which can replicate human cognition and build powerful applications for a large-scale impact in the F&B industry. We demonstrate how using science, big data, knowledge engineering and machine learning can enhance the way that the industry functions and improves productivity. We are looking for a Research Scientist, who not only has experience working with data and data technologies in a range of industry areas, but someone who has the ability to further develop these technologies and apply them in novel scenarios.

The successful candidate will be an independent thinker, able to see opportunities for the application of novel methodologies to improve the time to insight for scientific problems, particularly those with industrial relevance.

Responsibilities:
• Always stay on top of research happening food tech.
• Work with food scientists and generate research. Also, identify novel applications.
• Develop POC and prove the effectiveness.
• Lead a team of data scientists and engineers to build large-scale models for successful POC.
• Build a relationship with leading research organizations across the world.
• Publish research in top conferences.
• Hire and nurture high-quality talent.

Required Skills and Experience:
• Ph.D./M.S in Computer Science, Physics, Mathematics, or similar disciplines from a top university.
• Specialist in machine learning and general AI.
• Proven experience working in collaborative research programs.
• Experience coding in Python, including common data science toolkits, such as NumPy, Pandas etc.
• Distributed data analytics experience with Hadoop, HBase, Hive, and frameworks such as Spark
• Experience using different machine learning techniques and algorithms, ideally using common frameworks such as Scikit-learn, Tensorflow, Keras etc.
• Great communication skills, including experience presenting at scientific/technical conferences.
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good general scripting and programming skills.
• Data-oriented personality.

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