Associate Data Scientist
remoterocketship
- New York, New York, United States
- New York, New York, United States
Über
Extract, transform, aggregate, and analyze large and complex datasets using SQL, Python, R, Spark, and related technologies. Perform exploratory data analysis (EDA), feature engineering, and data validation to support analytics and modeling initiatives. Develop, evaluate, and maintain descriptive and predictive machine learning models using tools such as scikit-learn, Jupyter Notebooks, Python, R, and/or SAS. Apply statistical modeling and data mining techniques, including regression, classification, clustering, decision trees, and related methodologies. Utilize Generative AI and AI-assisted tools, including LLMs, coding assistants, and AutoML platforms, to improve analytical workflows and insight generation. Apply Generative AI techniques such as prompt engineering, text summarization, classification, and LLM-assisted analysis in business or research applications. Collaborate with stakeholders to translate business problems into analytical solutions and communicate findings effectively. Build and maintain business intelligence solutions and dashboards using Tableau, Power BI, or similar visualization platforms. Define metrics, validate data quality, and support semantic layer development to ensure accurate reporting and business insights. Follow responsible AI principles, including awareness of data privacy, bias mitigation, ethical AI usage, and model limitations. Requirements:
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field, with graduation expected in 2026. Minimum of 2 years of experience in data analysis, quantitative modeling, or data-driven decision-making through academic, internship, research, or professional experience. Proficiency in SQL and Python for data analysis, visualization, and modeling. Experience working with large datasets and distributed data processing tools such as Spark. Strong understanding of statistics and machine learning fundamentals, including model evaluation techniques. Hands-on experience with machine learning libraries and tools such as scikit-learn, Jupyter Notebooks, Python, R, and/or SAS. Exposure to Generative AI technologies and AI-assisted analytical workflows. Familiarity with business intelligence and visualization tools such as Tableau or Power BI. Strong analytical thinking, problem-solving, and communication skills. Benefits:
Opportunities to learn and develop every day through a wide range of programs. Internal digital platforms that promote self-learning. Development programs according to Leadership skills. Specialized training according to the role. Learning experiences with internal and external providers. Recognition programs for seniority, behavior, leadership, moments of life, among others. Financial wellness programs that will help you reach your goals in all stages of life. A flexibility program that will allow you to balance your personal and work life, adapting your working day to your lifestyle. Family benefits such as WellnessLine, thousands of Agreements and Discounts, Scholarship programs for your children, Aid Plans for different moments of life, among others.
Sprachkenntnisse
- English
Hinweis für Nutzer
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