Data Scientist-Customer Analytics

About Straive:-Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains.Data Analytics & Al Solutions, Data Al Powered Operations and Education & Learning form the core pillars of the company’s long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers.Data Analytics & Al Services : Our Data Solutions business has become critical to our client's success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future-fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them. With a client-base scoping 30 countries worldwide, Straive’s multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore.Website: https://www.straive.com/Designation: Data Scientist Job Location: Remote Qualifications: BE/ BTech/ ME/ MTech/ MSc Statistics Years of Experience: 2 to 8 yearsRole and Responsibilities:Marketing & Customer Analytics:Provide processes to measure, manage, and analyze marketing activities. Offer actionable insights and recommendations to optimize marketing ROI and performance efficiency. Use customer behavior data for market segmentation, predictive analytics, direct marketing, site selection, and customer relationship management.Data Science and Analysis:Apply scientific methods, processes, and systems to extract knowledge or insights from various forms of data (structured and unstructured). Employ multivariate statistical techniques such as regression, classification, and segmentation to analyze data.Machine Learning:Design, build, and deploy machine learning models focused on customer behavior, segmentation, churn prediction, recommendation systems, and lifetime value estimation. Collaborate with cross-functional teams (marketing, product, engineering) to identify business challenges and provide data-driven solutions. leverage machine learning techniques to extract insights from customer data, develop predictive models, and drive data-informed decision-making to improve customer engagement, retention, and lifetime value.Required Skills and Expertise:Proficiency in programming languages commonly used in data science such as SQL, Python R and Visualization tools like Power BI, Tableau etc. In-depth knowledge of multivariate statistical techniques, including regression, classification, and segmentation. Ability to analyze and interpret complex data sets. Expertise in handling structured and unstructured data. Skilled in SQL querying with data extraction, transformation, and loading (ETL) processes. Understanding of marketing metrics and the ability to analyze marketing activities. Experience in Consumer Analytics, Customer Analytics or Marketing Analytics working in CPG, FMCG industry would be an added advantage. Experience in providing insights for optimizing marketing strategies and operations. Ability to work effectively within a team, particularly in interdisciplinary settings. Experience in managing projects and delivering results within specified timelines. Strong analytical and problem-solving skills to address complex business and technical challenges.“Straive is an Equal Opportunity Employer. Our policy is clear: there shall be no discrimination based on age, disability, sex, race, religion or belief, gender reassignment, marriage/civil partnership, pregnancy/maternity, or sexual orientation. We are an inclusive organization and actively promote equality of opportunity for all with the right mix of talent, skills and potential. We welcome all applications from a wide range of candidates. Selection for roles will be based on individual merit alone.