Data Science Lead

1 week ago

Columbia, United States Blend360 Full time
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.

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
Qualifications
  • MS degree in Statistics, Math, Data Analytics, or a related quantitative field
  • 3+ years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization
  • Experience Managing a team
  • Experience with one or more Advanced Data Science software languages (R, Python, Scala, SAS)
  • Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
  • Experience with SQL and relational databases, query authoring and tuning as well as working familiarity with a variety of databases including Hadoop/Hive
  • 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


Additional Information

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