As a Data Scientist at Prevalent, you'll help turn complex data into clear, actionable insights that solve real business problems and support smarter decisions. Using advanced analytics, machine learning, and statistical methods, you'll build predictive models and data-driven solutions that enhance our key products— Exposure Management and Data Fabric. You'll work with data from various sources, uncover patterns, and deliver insights that improve how organizations manage risk and large-scale data. This role is a great opportunity to apply your data science skills to innovative, AI-powered products and make a direct impact on product development and business success.

Key accountabilities

Understanding business requirements through collaboration with SMEs and translating them into data

science solutions

Performing data assembly, cleansing, validation, and visualization
Applying statistical modelling, supervised and unsupervised machine learning, and mathematical

programming

Inspecting data for consistency and modifying designs as needed
Communicating predictions and findings through visualizations and reports
Creating prototypes for data manipulations, visualizations, and modelling
Validating designs with SMEs and iterating based on feedback
Ensuring software implementation matches design expectations through testing
Keeping up with industry trends and following a personal education plan for technology and solution

architecture

Skills and Experience

Relevant experience working in Data Science
Experience in working with Big Data and common data science tools such as R, Python, Spark etc
Self-motivated individual capable of working in a fast-paced environment
Great verbal and written communication skills
A strong analytical mind-set
Good understanding and expertise in processing large datasets
Good working knowledge in implementation of various ML algorithms in big data environment,

advanced ML concepts like ANN, Deep learning etc

Understanding of data visualization tools, such as D3.js, Tableau, etc

• Familiarity with Scala, HIVE is desired • Good scripting and programming skills; SQL proficiency

Understanding of and proficiency in NLP
Understanding of a range of statistical and machine learning techniques and algorithms, such as

logistic regression, KNN, decision trees, SVM, CNN, etc

Good understanding of the process workflow:

o Problem definition to hypothesis building
o Prototype model building using python/R o Implementation of ML problems in big data. o Performance Monitoring & Evaluation of System

Education

Bachelor’s/ Master’s in Engineering, Science, or Mathematics

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Data Scientist