Job Description for Senior Data Scientist: 5 years of relevant experience Insights. Campaigns. a senior data scientist you will be deploying advanced algorithms to build predictive models create or apply frameworks and take your team of data scientists down the right path to solve a business problem.
Job Role:
Data scientist will develop and maintain statistical models apply machine learning techniques and build highquality predictive/prescriptive systems.
The Sr data scientist will also make technology and business recommendations as well as develop key insights based on data analysis.
The candidate must be able to partner with business stakeholders in order to curate business problem statements and guide which business priorities using data.
Skills:
Proficiency in predictive modeling feature engineering Hypothesis testing and Machine Learning (Decision Trees GBM XGBoost GLM modeling Forecasting Scorecard development Clustering)
Experience in A/B Testing campaign design and scaling data science models into production level model that can handle complex realtime data
Hands on programming experience on Python
Good to have experience in SAS /R/ SQL
Experience in working on different analytics Techstacks (AWS/ Azure/ GCP) Experience in analytics project management and working with business stakeholders Expertise in collating data from different sources data mining and data wrangling
Must have good presentation skills
Experience:
Development of Predictive analytics models using machine learning and linear algorithms.
Have worked on classification regression and forecasting business problem statements
Expertise in model training and validation to improve higher accuracy and model stability
Experience in maintaining analytics model and develop analytics governance frameworks Insights. Campaigns. Results.
Have worked in different technology stacks (Cloud/on Prem) for model deployment and production
Experience in working with business stakeholders and for curation of analytics problems
Must have analytics delivery experience on Business Analytics Data science and Natural Language processing Prior experience in Big Data projects
Must have worked on banking use cases like cross sell upsell customer retention customer acquisition customer servicing personalization ATM optimization Branch analytics
Own Data assessment for analytics and building data foundations for analytics use cases.
Exposure to Artificial intelligence techniques and use cases
Experience in use of language models (NLP) for business
5 experience in data science and business analytics
Academic Qualifications:
Engineering / BTech or Masters in Statistics
Good to have Masters and/or Certifications in Analytics
Must have worked with as data science profiles in the past
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