- Experience in machine learning based predictive modeling projects
- Define project objectives and scope to deliver the projects satisfactorily
- Deliver projects within budget and time
- Leverage internal horizontal teams to enhance delivery such as Automation teams, Transition, Quality
- Network internally across regions to discover and implement best practices
- Should have hands on experience with machine learning models like Gradient Boosting, Collaborative filtering, Bayesian Methods, Random Forest, SVM, Markov Models etc.
- Able to understand and translate business and product questions into analytics projects
- Should have a mix of technical, development, and program management skills
- Strong business acumen
- Expert in querying and analyzing big data using Hive, Python, SQL, Scope and/or C#
- Experience working with unstructured big data (Hadoop and/or Cosmos)
- Experts in advanced Excel functions (e.g., creating formulas, pivot tables) and PowerBI
- Prior knowledge of data modeling and processing techniques for big data systems
- Solid understanding of BI and data solutions, including Power-pivots, cubes, and datamarts.
- Self-motivated, agile and driven to think out-of-the-box
- Ability to influence diverse audiences and build strong partnerships with stakeholders
- Ability to articulate vision, requirements, and benefits to business and engineering partners
- BE/B.Tech/MCA/M. Tech. /MSc/Ph.D. in Computer Science, Engineering Disciplines, Mathematics, Statistics with computer programming skills, Algorithm design. (Masters/PhD preferred)
- Hands on expertise in predictive analytics & model building.
- At least 5+ years of hands-on experience in the Machine Learning, Predictive modelling, Data Mining techniques and methodologies, algorithm design etc.
- Hands-on experience in:
- R/Python, SAS, SPSS
- Machine learning models like Gradient Boosting, Collaborative filtering, Bayesian Methods, Random Forest, SVM, Markov Models etc.
- Predictive model building (desired area – Sales & Marketing)
- Experience in using MS stack/Open Source Applications
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