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Description
Role Overview We are looking for a highly skilled and motivated Senior Data Scientist to join our team. In this role, you will design, develop, and implement advanced data models and algorithms that drive strategic decision-making across the organization. You will work closely with product, engineering, and business teams to uncover insights and deliver data-driven solutions that enhance the performance and scalability of our products and services. Key Responsibilities Develop, deploy, and maintain machine learning models and advanced analytics pipelines. Analyze complex datasets to identify trends, patterns, and actionable insights. Collaborate with cross-functional teams (Engineering, Product, Marketing) to define and execute data science strategies. Build and improve predictive models using supervised and unsupervised learning techniques. Translate business problems into data science projects with measurable impact. Design and conduct experiments, A/B tests, and statistical analyses to validate hypotheses and guide product development. Create dashboards and visualizations to communicate findings to technical and non-technical stakeholders. Stay up-to-date with industry trends, best practices, and emerging technologies in data science and machine learning. Ensure data quality and governance standards are maintained across all projects. Required Skills And Qualifications 68 years of hands-on experience in Data Science, Machine Learning, and Statistical Modeling. Proficiency in programming languages such as Python, R, and SQL. Strong foundation in data analysis, data wrangling, and feature engineering. Expertise in building and deploying models using tools such as scikit-learn, TensorFlow, PyTorch, or similar frameworks. Experience with big data platforms (e.g., Spark, Hadoop) and cloud services (AWS, GCP, Azure) is a plus. Deep understanding of statistical techniques including hypothesis testing, regression, and Bayesian methods. Excellent communication skills with the ability to explain complex technical concepts to non-technical audiences. Proven track record of working on cross-functional projects and delivering data-driven solutions that impact business outcomes. Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field. Experience with NLP, computer vision, or deep learning techniques. Knowledge of data engineering principles and ETL processes. Familiarity with version control (Git), agile methodologies, and CI/CD pipelines. Contributions to open-source data science projects or publications in relevant fields. (ref:hirist.tech) Show more Show less
