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 constraintsProblem-solve with practice leaders to translate the business problem into a workable Data Science solution; propose different approaches and their pros and consWork with practice leaders to get stakeholder feedback, get alignment on approaches, deliverables, and roadmapsYou will work as part of our global Data Science team to provide data driven AI solutions for our customers using state-of-the-art Machine Learning methods and tools.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 technologiesAssemble 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 issuesConduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision makingTrain, validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and toolsDocument predictive models/machine learning results that can be incorporated into client-deliverable documentationAssist client to deploy models and algorithms within their own architecture
Qualifications
MS degree in Statistics, Math, Data Analytics, or a related quantitative field2+ years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimizationExperience with one or more Advanced Data Science software languages (Python, R, SAS)Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approachesExperience with SQL and relational databases, query authoring and tuning as well as working familiarity with a variety of databases including Hadoop/HiveExperience with spark and data-frames in PySpark or ScalaStrong 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
Additional Information
All your information will be kept confidential according to EEO guidelines.#
Associated topics:
data administrator, data analytic, data architect, data center, data engineer, data integration, data integrity, data quality, database, mongo database