- Data Science
- Data Scientist
- Data Warehousing
- machine learning
- architectural design
This position can be 100% remote. The opening is W2 permanent only. The client is not able to provide sponsorship. No third parties or c2c.
The Data Scientist uses data science tools and advanced data analysis techniques to create insights, create machine learning algorithms, and design predictive modeling processes to solve tangible business problems that lead to increased revenue, increased efficiencies and exceptional customer experience.
The Data Scientist works with a team of Data Engineers and Architects, conceives solutions, builds consensus, and effectively presents solutions to the stakeholders and leadership team. The Data Scientist leverages data, tools, technical, and business knowledge to drive the development of data solutions at the portfolio and enterprise levels. Portfolio and solution designs and roadmaps will encompass intelligent use of data through data science, machine learning and other predictive/prescriptive functions and support the generation of revenue and enable cost savings/avoidance. The Data Scientist will maintain a competitive edge through continuous self-development as a core competency and freely sharing relevant information for the benefit of the entire Technology and Data Team.
- Create new, experimental frameworks to advance data management practices.
- Responsible for leading the data collection, cleansing and processing both structured and unstructured raw data.
- Employ machine learning, statistical modeling and use data science tools (e.g. DataRobot) to derive insights from the data.
- Perform descriptive statistics to derive insights from the data. Use data visualization to build a story with insights and present it to Technology and Leadership teams.
- Work closely with the product team and leadership to drive real-time model implementations and new feature creations.
- Establish scalable, effective, automated processes for large data analyses, model development, model validation, and model implementation.
- Responsible for data architectural design, low-level tasks for development, data & model validation, acceptance testing, and production deployment.
- Develop data management standards, policies, controls, governance procedures, and best practices for use within enterprise systems and applications; including design, development, tuning, deployment, and maintenance of information and advanced data analytics and intelligence.
- Deliver an ML project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organization.
- Design and implement metrics and dashboards to identify trends and opportunities and drive key business decisions.
- Apply your expertise in quantitative analysis, data mining, and the presentation of data to extract actionable business insights.
- Experience in driving an experimental idea to a proof-of-concept to a launched product.
- Derive statistically valid insights from data science models to improve product development, marketing, sales, or business strategies.
- Participate in the planning of solutions and deployment strategies including proof of concepts, pilots, conversions, upgrades, and rollouts.
- Implement automation procedures to simplify daily systems support activities.
- Present recommendations and technical information to teams with varied level of technical knowledge and/or upper management.
- Maintain a competitive edge through continuous self-development as a core competency and freely share relevant information for the benefit of the entire Technology Team.
- Bachelor’s degree in Computer Science, MIS, engineering or related program or directly related experience and certification beyond minimums will be considered.
- Minimum 6+ years of directly related experience in enterprise environment required.
- Data Science and Analytics experience required and certification is preferred.
- 3+ years of industry experience in predictive modeling and analysis
- Hands-on experience to build and deploy models using Data Science tools like DataRobot
- Experience with AI and ML solutions for data research and analytics is required.
- Snowflake solution design/implementation experience required.
- Knowledge of common technology solutions from leading technology providers is required.
- Experience in the design, implementation and maintenance of Data Warehousing solutions required.
- Ability to structure a problem, gather supporting data with scripting and large data warehousing and write strong narratives to convey findings
- Extremely strong analytical and problem-solving skills.
- Great attention to detail.
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
- Excellent communication skills, sharing technical details with team members, project teams, and stakeholders and produces ideas, solutions, and materials for Technology Team Leadership.
- Self-starter and works with minimal supervision with excellent time management, documentation, and relationship management skills.