Urgently Hiring: Sr. Data Scientist
We're searching for a qualified Sr. Data Scientist! This role is 100% remote, giving you full control over your work environment. This position requires a strong and diverse skillset in relevant areas to drive success. This role offers a salary package of a competitive salary, commensurate with experience. Â Â Senior Data Scientist - will work on building AI/ML-powered data products. Work with seasoned Decision Science professionals in creating cutting-edge solutions to solve fraud, risk, and marketing-related problem statements. We are looking for an energetic and experienced person as a Data Scientist. The chosen candidate will be responsible for developing and enhancing all aspects of data mining, predictive analytics, risk rule engine, collection, and fraud solutions development. Experience in Banking and Financial Services, Customer Experience is a plus.
Responsibilities:
 Focus on developing a clear and concise analytical approach to problem-solving.
 Work with the data engineering team in framing your data requirement and setting up the data pipelines from different source systems into a data warehouse which will feed into various analytics use cases.
 Stay up-to-date with the latest advancements in data science, and machine learning, and proactively apply new methodologies and technologies to enhance existing solutions.
 Develop, enhance, and maintain predictive models of credit risk, fraud, and collections.
 Manage the delivery of projects including timely communication, setting milestones, and tracking.
 Generate actionable insights for business KPI improvements.
 Self-manage your priorities and deliverables while working in a fast-paced, startup environment.
 Build and prototype analysis pipelines iteratively to provide insights at scale, on tools such as Python, Pyspark, Streamlight, and AWS cloud.
 Coach and mentor junior team members within data science and data engineering functions.
 Collaborate with tech and product team to deploy machine learning models into production and their integration with the customer-facing applications.
Requirements:
 Minimum 4 years of experience with machine learning, analytics consulting, and product development.
 Education: PhD, Masters in Economics, Statistics, Mathematics or bachelors in computer science or quantitative fields from premier institutes.
 Must have 4+ years of experience in building predictive models; have built and deployed data products as microservices.
 Experience in driving the implementation of solutions, data, and algorithms on AWS cloud leveraging different services.
 You have a solid foundation in computer science and strong competencies in data structures, algorithms, and software design, expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
 You are experienced in one or more of the following areas: Machine Learning (ML) models, ML infrastructure, Natural Language Processing, or Deep Learning.
 You are proficient in one or more data-oriented programming languages/tools (e. g. Python packages such as Pandas, Scikit-learn, and Jupyter) and database languages (e. g. SQL).
 Prior experience with data visualization tools, such as D3.js, GGplot, etc.
 Proficiency with any one NoSQL database such as MongoDB, Cassandra, and HBase.
 You have a keen interest in financial services and a passion for shipping high-quality consumer-facing products.
 Proficiency in machine learning techniques, including supervised and unsupervised learning, feature engineering, and model evaluation; exposure to generative AI is a plus. Apply Job! Your Future Starts HereDon't miss out on this exciting role. We are looking forward to hearing from you. Apply now!
Apply Now
Responsibilities:
 Focus on developing a clear and concise analytical approach to problem-solving.
 Work with the data engineering team in framing your data requirement and setting up the data pipelines from different source systems into a data warehouse which will feed into various analytics use cases.
 Stay up-to-date with the latest advancements in data science, and machine learning, and proactively apply new methodologies and technologies to enhance existing solutions.
 Develop, enhance, and maintain predictive models of credit risk, fraud, and collections.
 Manage the delivery of projects including timely communication, setting milestones, and tracking.
 Generate actionable insights for business KPI improvements.
 Self-manage your priorities and deliverables while working in a fast-paced, startup environment.
 Build and prototype analysis pipelines iteratively to provide insights at scale, on tools such as Python, Pyspark, Streamlight, and AWS cloud.
 Coach and mentor junior team members within data science and data engineering functions.
 Collaborate with tech and product team to deploy machine learning models into production and their integration with the customer-facing applications.
Requirements:
 Minimum 4 years of experience with machine learning, analytics consulting, and product development.
 Education: PhD, Masters in Economics, Statistics, Mathematics or bachelors in computer science or quantitative fields from premier institutes.
 Must have 4+ years of experience in building predictive models; have built and deployed data products as microservices.
 Experience in driving the implementation of solutions, data, and algorithms on AWS cloud leveraging different services.
 You have a solid foundation in computer science and strong competencies in data structures, algorithms, and software design, expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods.
 You are experienced in one or more of the following areas: Machine Learning (ML) models, ML infrastructure, Natural Language Processing, or Deep Learning.
 You are proficient in one or more data-oriented programming languages/tools (e. g. Python packages such as Pandas, Scikit-learn, and Jupyter) and database languages (e. g. SQL).
 Prior experience with data visualization tools, such as D3.js, GGplot, etc.
 Proficiency with any one NoSQL database such as MongoDB, Cassandra, and HBase.
 You have a keen interest in financial services and a passion for shipping high-quality consumer-facing products.
 Proficiency in machine learning techniques, including supervised and unsupervised learning, feature engineering, and model evaluation; exposure to generative AI is a plus. Apply Job! Your Future Starts HereDon't miss out on this exciting role. We are looking forward to hearing from you. Apply now!
Apply Now