IT Sr. Data Scientist

Title: IT Sr. Data Scientist Location: Remote NO VISA OR C2C Role Summary Gains experience in collaborating with business partners to develop predictive analytic solutions that enable data-driven strategic decision-making. Utilizes data science techniques to manipulate large structured and unstructured data sets, identify patterns in raw data, and develop models to predict the likelihood of a future outcome and/or to optimize business solutions. Focus at this level is on gaining industry knowledge, development of predictive analytics techniques, some experience in developing GenAI/LLM based tools, and obtaining experience in storytelling with data. Job Responsibilities Applies data science techniques; gains confidence in skill application using analytics and data science techniques to manipulate large structured and unstructured data sets in order to generate insights to inform business decisions. Identifies and tests hypotheses, ensuring statistical significance, as part of building predictive models for business application and desire to develop GenAI/LLM (OpenAI) based tools. Translates quantitative analyses and findings into accessible visuals for non technical audiences, providing a clear view into interpreting the data. Gains experience in enabling the business to make clear tradeoffs between and among choices, with a reasonable view into likely outcomes. Assists in customizing analytic solutions to specific client needs. Responsible for smaller components of projects considered low to moderate complexity and may work on smaller components of complex projects. Engages with the Data Science community. Participates in cross functional working groups. Preparation, Training & Experience Data extraction and manipulation skills, EDA, transformations, comfort manipulating and analyzing high-volume, high-dimensionality data from varying sources. Experience developing algorithms and products with generalized linear models (GLM), clustering (KNN), Random Forest, XGBoost, time series (ARIMA), NLP, Process and Pattern Mining using popular Client frameworks, Python (Pandas, Numpy, scikit-learn, PyTorch), SQL, Spark, TensorFlow, project versioning in git. Foundational knowledge of predictive analytics tools. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Has a value driven perspective with regard to understanding of work context and impact. Competencies typically acquired through a PhD (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and 3 years of relevant experience.