Details:

Responsibilities

• Work in a startup-like, nimble, fast-paced thriving entrepreneurial environment to create data analytics solutions and connect to business needs and commercial strategies. 
• Work closely with a team of energized Lead Software Engineers and technologists based in both India and U.S. with diverse backgrounds, to tinker with new ideas in an agile, collaborative, and “fast to fail” fashion.
• Stay on the cutting edge of technology evolution in the data science and engineering area, and closely connect with external technology partners and innovations.
• Proactively collaborate with business partners and domain experts from various functions (R&D, marketing, sales, IT, supply chain, etc.) to identify and formulate problems and innovation opportunities that can be enabled by the predictive and deep data analytics.
• Architect, rapid prototype and test data analytics solutions in a POC (proof of concept) scale to operationalize the outcomes of the predictive modeling and validate the results. 

Basic Qualifications

• Bachelor’s degree in Data Science/Data Analytics, Computer Science, Operations Research, Applied Mathematics, Statistics or related science and technical field.
• 2+ years of hands-on experience in developing predictive and deep data analytics solutions and optimization scenarios.

Preferred Qualifications

• 5+ years of hand-on experience in developing predictive and deep data analytics solutions for real-world business operation and commercial uses (e.g., customer analytics, supply chain and logistics, predictive maintenance, etc.).
• Master’s or PhD degree in Data Science/Data Analytics, Computer Science, Operations Research, Applied Mathematics, Statistics or related science and technical field.
• Background in Chemical or other Engineering disciplines or Chemistry.
• Proficiency with modern statistical modeling (regression, boosting trees, random forests, etc.), machine learning (text mining, neural network, NLP, etc.), optimization (linear optimization, nonlinear optimization, stochastic optimization, etc.) methodologies.
• Background in solving problems in the B2B world including supply chain optimization, predictive service etc.
• Proficiency with open-source data analytics toolsets such as R, Python, etc.
• Experience with advanced data analytics platform tools such as SAS, Azure ML, Rapidminer, MATLAB, KNIME, etc.
• Familiar with modern data analytics architecture and data engineering technologies (Hadoop, SQL and No-SQL databases, ETL techniques, etc.)
• A strong business focus, ownership and inner self-drive to bring connected offerings to real-world customers with tangible impact.
• Comfortable working in an agile and fast-paced environment and creating order from ambiguity.
• Ability to work with multidisciplinary and passionate team members to do whatever it takes to get the job done.
• A life-long learner who constantly updates skills (certifications earned and a portfolio of self-driven analytics problem solving examples in repositories like GitHub).

Min. Qualification:

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Skills Required:

analytics, boosting, deep learning, etl, hadoop, machine learning, matlab, No SQL, optimization, predictive model, python, r, random forest, regression, sas, sql