Role
Company
What makes you a great fit:
- 2+ years of experience as a data scientist.
- Hands-on expertise in Predictive Modelling, Machine Learning, Customer Segmentation, EDA Etc.
- Proficiency with SQL, Python & R.
- In-depth understanding of Feature engineering and selection approaches, Segmentation or stratified analyses and data transformation approaches.
- Strong grasp of numbers, statistics, mathematical concepts, and algorithms.
- Knowledge of data structures, relational data, and big data platforms.
- Ability to debug, troubleshoot and optimize existing code base.
- Knowledge of working with Github and MLops principles.
- Demonstrate experience and understanding of Machine Learning, e.g.: linear/logistics regression, random forest, XGBoost, SVM, neural networks, etc.
- Experience of working within a multicultural, global environment.
- Experience of working in a fast moving and changing environment.
- Experience with NLP and linguistic approaches for retrieval, interpretation, and pushing of insight from scientific literature.
- Strong communication skills, both written and verbal
- Ability to manage stakeholders' expectations and work in a high-pressure environment.
- Demonstrate strong ownership & commitment to the cause of customer success.
- A team player capable of high performance, flexibility in a dynamic working environment and the ability to lead
Valiance brings years of experience in successfully applying Datascience & Machine Learning to wide variety of business problems globally. We work with single minded goal of helping our clients achieve business excellence through intelligent use of data sources-internal or external. In doing so, we have worked with marquee global brands in Financial Services, Management Consulting, Metals & Mining, Power Generation and Healthcare verticals. We have had
★ Product teams partner with us to improve product features using machine learning.
★ Business leaders consult us on problem analysis - what, why, what-if questions
★ Data Science & Technology teams engage us for data engineering, model development & deployment.
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