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Company:
Blend
Posted: July 1, 2024
Company Description
Blend360 is a world class marketing, analytics, and technology company that delivers the best results for our clients. Our primary focus is Data Sciences; leveraging data and applied mathematics to solve our clients' business challenges. Blend360 is known for our exceptional people, our get-it-done mentality, and delivering high impact and sustainable results. 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.
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
Develop a project plan including milestones, dates, owners, and risks and contingency plans
QA MMM input and output data sets. Translate datasets from human generated XLS to formats for MMM input. Translate MMM output to human readable outputs such as XLS and ppt.
QA data. Answer MMM questions from the marketing, category, channel, and merchandizing teams with the help of the Neustar MMM data scientists.
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
Qualifications
MS degree in Statistics, Math, Data Analytics, or a related quantitative field
2+ years post grad professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization (If you are a new grad - please apply to our All Star Positions)
Strong Communication Skills and the ability to work under tight deadlines
Sufficient high-level knowledge of MMM input and output formats and how MMM works
Strong SQL, Python and Excel skills
Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
Strong SQL, Python and Excel.
Ability to interpret MMM output.
Ability to work in PST
Experience with spark and data-frames in PySpark or Scala
Strong problem-solving skills; ability to pivot complex data to answer business questions. Proven ability to visualize data for influencing.
Comfortable with cloud-based platforms (AWS, Azure, Google)
Experience with Google Analytics, Adobe Analytics, Optimizely a plus
•
Blend360 is a world class marketing, analytics, and technology company that delivers the best results for our clients. Our primary focus is Data Sciences; leveraging data and applied mathematics to solve our clients' business challenges. Blend360 is known for our exceptional people, our get-it-done mentality, and delivering high impact and sustainable results. 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.
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
Develop a project plan including milestones, dates, owners, and risks and contingency plans
QA MMM input and output data sets. Translate datasets from human generated XLS to formats for MMM input. Translate MMM output to human readable outputs such as XLS and ppt.
QA data. Answer MMM questions from the marketing, category, channel, and merchandizing teams with the help of the Neustar MMM data scientists.
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
Qualifications
MS degree in Statistics, Math, Data Analytics, or a related quantitative field
2+ years post grad professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization (If you are a new grad - please apply to our All Star Positions)
Strong Communication Skills and the ability to work under tight deadlines
Sufficient high-level knowledge of MMM input and output formats and how MMM works
Strong SQL, Python and Excel skills
Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
Strong SQL, Python and Excel.
Ability to interpret MMM output.
Ability to work in PST
Experience with spark and data-frames in PySpark or Scala
Strong problem-solving skills; ability to pivot complex data to answer business questions. Proven ability to visualize data for influencing.
Comfortable with cloud-based platforms (AWS, Azure, Google)
Experience with Google Analytics, Adobe Analytics, Optimizely a plus
•
Read the full job description and apply online on the recuiter's web-site
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