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IT Sr. Data Scientist
2 months ago
LOCATION: Remote any US time zone
REQUIRED: Seasoned PhD level candidates. Strong communications skills, expected to communicate and influence business leaders and help stakeholders make favorable business decisions. SME in predictive modeling and discussing cost benefits of presented solutions.
Job Introduction:
The Technology Data Science & Data Governance team is looking for a highly motivated Data Scientist to join at an exciting time as we embark on developing AI/ Machine Learning tools to support Technology Enablement portfolios, employee digital experience and productivity across all Lines of Business. This person will collaborate closely with Technology teams, LOB Operations, other Data Scientists, and IT Product owners. They will leverage data and advanced techniques to develop, implement and analyze predictive models that enable data-driven, strategic decision-making. This role requires expertise in a broad range of predictive analytics techniques and their application to business opportunities - both, large impact and smaller "quick hits" complex engagements. A successful candidate will be organized, creative, and interested in solving business problems using data and analytics. They will have the right mix of analytical, technical, and communication skills to thrive in a fast-paced environment.
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 Master`s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience or may be acquired through a Bachelor`s degree and 3+ years of relevant experience.
EEO:
"Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of - Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans."
