Company:
Blend360
Location: Columbia
Closing Date: 05/12/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Job Description
We are looking for a Lead Data Scientist to join our team. At Blend our Data Scientists work with business leaders to solve our clients’ business challenges. We work with clients in marketing, revenue management, customer service, inventory management and many other aspects of modern business. Our Data Scientists have the business acumen to apply Data Science to many different business models and situations.
We expect the Data Scientists to be excellent communicators with the ability to describe complex concepts clearly and concisely. They should be able to work independently in gathering requirements, developing roadmaps, and delivering results.
Technical know-how: Our Data Scientists have a broad knowledge of a variety of data and mathematical solutions. Our work includes statistical analyses, predictive modeling, machine learning, and experimental design. We evaluate different sources of data, discover patterns hidden within raw data, create insightful variables, and develop competing models with different machine learning algorithms. We validate and cross-validate our recommendations to make sure our recommendations will perform well over time.
Conclusion: If you love to solve difficult problems and deliver results; if you like to learn new things and apply innovative, state-of-the-art methodology, join us at Blend360.
Responsibilities
Understand client needs and customize existing business processes to meet client needs.
Promptly address client concerns and professionally manage requests.
Work as a strategic partner with leadership teams to support client needs.
Work with practice leaders and clients to understand business problems, industry context, data sources, potential risks, and constraints
Problem-solve with practice leaders to translate the business problem into a workable Data Science solution; propose different approaches and their pros and cons
Work with practice leaders to get stakeholder feedback, get alignment on approaches, deliverables, and roadmaps
Develop a project plan including milestones, dates, owners, and risks and contingency plans
Create and maintain efficient data pipelines, often within clients’ architecture. Typically, data are from a wide variety of sources, internal and external, and manipulated using SQL, spark, and Cloud big data technologies
Assemble large, complex data sets from client and external sources that meet functional business requirements.
Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Perform data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform. Be able to summarize and describe data and data issues
Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making
Train, validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and tools
Document predictive models/machine learning results that can be incorporated into client-deliverable documentation
Assist client to deploy models and algorithms within their own architecture
We are looking for a Lead Data Scientist to join our team. At Blend our Data Scientists work with business leaders to solve our clients’ business challenges. We work with clients in marketing, revenue management, customer service, inventory management and many other aspects of modern business. Our Data Scientists have the business acumen to apply Data Science to many different business models and situations.
We expect the Data Scientists to be excellent communicators with the ability to describe complex concepts clearly and concisely. They should be able to work independently in gathering requirements, developing roadmaps, and delivering results.
Technical know-how: Our Data Scientists have a broad knowledge of a variety of data and mathematical solutions. Our work includes statistical analyses, predictive modeling, machine learning, and experimental design. We evaluate different sources of data, discover patterns hidden within raw data, create insightful variables, and develop competing models with different machine learning algorithms. We validate and cross-validate our recommendations to make sure our recommendations will perform well over time.
Conclusion: If you love to solve difficult problems and deliver results; if you like to learn new things and apply innovative, state-of-the-art methodology, join us at Blend360.
Responsibilities
Understand client needs and customize existing business processes to meet client needs.
Promptly address client concerns and professionally manage requests.
Work as a strategic partner with leadership teams to support client needs.
Work with practice leaders and clients to understand business problems, industry context, data sources, potential risks, and constraints
Problem-solve with practice leaders to translate the business problem into a workable Data Science solution; propose different approaches and their pros and cons
Work with practice leaders to get stakeholder feedback, get alignment on approaches, deliverables, and roadmaps
Develop a project plan including milestones, dates, owners, and risks and contingency plans
Create and maintain efficient data pipelines, often within clients’ architecture. Typically, data are from a wide variety of sources, internal and external, and manipulated using SQL, spark, and Cloud big data technologies
Assemble large, complex data sets from client and external sources that meet functional business requirements.
Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Perform data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform. Be able to summarize and describe data and data issues
Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making
Train, validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and tools
Document predictive models/machine learning results that can be incorporated into client-deliverable documentation
Assist client to deploy models and algorithms within their own architecture
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