Machine Learning Engineer
#MachineLearning #BigData #DataScience #DeepLearning
Roles and Responsibilities
  • Solve challenging real world problems using bleeding edge technology and tools.
  • Work on machine learning based solutions around multiple domains like Sales Forecasting, Customer Propensity, Price Optimization, Classification Models, Recommender Systems, Sentiment Analyzer Models, Contextual Conversation Modelling.
  • Get End-to-end ownership of deliverables - POC to production.
  • Work directly with customers & users - understand their needs and provide expert recommendations.
  • Work with a team of exceptionally talented and dedicated Data Scientists and Engineers.
  • BYOP - Bring your own process. We like new things.
Qualifications and Skills
  • Bachelors or Masters Degree in Computer Science/Information Technology/Statistics/Mathematics or relevant streams.
  • 2+ years hands-on experience.
  • Experience in Regression, Machine Learning, Deep learning etc.
  • Expert level proficiency in at least one of R and Python.
  • Ability to discover effective solutions to complex problems. Strong skills in data-structures and algorithms.
  • Experience of working on a project end-to-end: problem scoping, data gathering, modeling, insights, and visualizations.
  • Problem-solving: Ability to break the problem into small problems and think of relevant techniques which can be explored & used to cater to those.
  • Intermediate to advanced knowledge of machine learning, probability theory, statistics, and algorithms.
Benefits
Flexible working environment.
Health Insurance Coverage.
Accelarated Career Planning.
Competitive compensation and perks.
Rewards and Recognition.
Competitive Environment.
Location
A world without boundaries - we hire globally and offer remote and hybrid working options. We are headquartered in Pune (India) and the Silicon Valley.
Equal Opportunity Employer
Mindstix is committed to an inclusive and diverse work environment. We do not discriminate based on race, colour, ethnicity, ancestry, national origin, religion, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any other legally protected status.
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