Job Description

Sigmoid enables business transformation using data and analytics, leveraging real-time insights to make accurate and fast business decisions, by building modern data architectures using cloud and open source. Some of the world’s largestdata producers engage with Sigmoid to solve complex business problems. Sigmoid brings deep expertise in data engineering, predictive analytics, artificial intelligence, and DataOps. Sigmoid has been recognized as one of the fastest growing technology companies in North America, 2021, by Financial Times,Inc. 5000, and Deloitte Technology Fast 500. Offices : New York | Dallas | San Francisco | Lima | Bengaluru

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Data Scientist Why Join Sigmoid?

• Sigmoid provides the opportunity to push the boundaries of what is possible by seamlessly combining technical expertise and creativity to tackle intrinsically complex business problems and convert them into straight-forward data solutions.
• Despite being continuously challenged, you are not alone. You will be part of a fast-paced diverse environment as a member of a high-performing team that works together to energize and inspire each other by challenging the status quo
• Vibrant inclusive culture of mutual respect and fun through both work and play

Qualifications

• A B-Tech/M-Tech/MBA degree from a top-tier institute, ideally in a quantitative field.
• 3-7 years of hands-on experience in applied Machine Learning (ML), AI, and analytics.
• Extensive background in scientific programming with languages like Python, R, SQL, NoSQL, Spark, and experience in cloud technologies (AWS, Azure, GCP).
• Deep understanding of machine learning, deep learning, data mining, and statistical concepts.
• Hands-on experience in developing solutions using these concepts and tools.
• Expertise with ML libraries such as numpy, pandas, scikit-learn, TensorFlow, scrapy, BERT, and others.
• Ability to understand complex business challenges, especially in domains like Supply Chain, Manufacturing, CPG, and Marketing.
• Provide actionable solutions and insights to clients in these industries.
• Extensive background in scientific programming with languages like Python, R, SQL, NoSQL, Spark, and experience in cloud technologies (AWS, Azure, GCP).Language python , SQL is sufficient

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