The Manager, Regulatory and PV Delivery leads regulatory strategy and deliverables, ensuring compliance while mentoring junior staff and supporting business development efforts.
Data Science Manager (Multiple vacancies)
📜 Description
- Leads projects or workstreams translating business problems into data science solutions.
- Proposes various approaches and oversees delivery of predictive analytics, models, and algorithms.
- Develops project plans with milestones, risks, and contingency plans.
- Builds analytics tools to provide insights into customer acquisition and operational efficiency.
- Conducts statistical data analysis and documents key insights for decision-making.
- Trains and validates predictive models and machine learning algorithms.
🛠️ Requirements
- Master's degree in Statistics, Mathematics, Computer Science, Data Science, Data Analytics, Business Analytics, or a related quantitative field.
- Two years of related work experience in advanced data science.
- Experience with predictive modeling and statistical analysis.
- Proficiency in advanced data science software languages and tools.
- Knowledge of query languages, semi-structured data, and relational databases.
- Experience with cloud-based computing and storage platforms.
Full job description
Company Description
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.
Job Description
Duties: Leads projects or workstreams that translate business problems into workable data science solutions, proposing different approaches and overseeing delivery of predictive analytics, models, and algorithms. Develops project plans, including milestones, dates, owners, risks, and contingency plans. Assembles and evaluates for applicability large, complex data sets from clients and external sources, managing the selection criteria and process for identifying the data and necessary data transformations that meet functional business requirements. Builds analytics tools to communicate actionable insights into customer acquisition, customer retention, margin improvement, operational efficiency, and other key business performance metrics. Performs data cleaning/hygiene and quality control, and integrates data from both client internal and external data sources on advanced data science platforms. Summarizes and describes data and data issues. Conducts statistical data analysis, including exploratory data analysis and data mining, and document key insights and findings toward decision-making. Trains, validates, and cross-validates predictive models and machine learning algorithms using state of the art data science techniques and tools. Documents predictive models/machine learning results that can be incorporated into client-deliverable documentation. Assists clients to deploy models and algorithms within their own architecture. Manages data analyst project work.
Salary Range: $139,547-$160,000
Remote work permitted from any U.S. location. Domestic travel 10% of time to unanticipated client sites for meetings and project-related matters.
Apply to jobs@blend360.com w/ subject “Data Science Manager.”
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Qualifications
Requirements: Master’s degree in Statistics, Mathematics, Computer Science, Data Science, Data Analytics, Business Analytics, or a related quantitative field. Two years of related work experience in advanced data science, to include two years of experience with each of the following predictive modeling and statistical analysis; advanced data science software languages and tools; query languages, semi-structured data, and relational databases, including query authoring and tuning; and cloud-based computing and storage platforms.
Additional Information
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