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Senior Data Scientist

Senior Data Scientist
NY, New York or Silver Spring

Job Description

#59299

Title: Senior Data Scientist, New York or Maryland

Type: perm, full time

Location: Anywhere on East Coast – preferably commutable to NYC or MD office should they ever return to office

Must Have: Master’s or PhD degree in a quantitative field (statistics, finance, econometrics, etc.), Min 5+ y proven business experience and technical expertise in data science, applied experience related to customer lifetime value projection, including methodologies such as survival analysis; RFM(recency, frequency, monetary)/BTYD (buy til you die) frameworks; Pareto/NBD models and other parametric approaches/distributions; and non-parametric approaches such as neural networks (CNN, LSTM, etc.), Experience with time-series analysis, time-based validation, hypothesis testing, clustering, regression, & classification, Experience cleansing and preparing large, complex datasets for analysis, Expertise in statistical programming languages such as R or Python (StatsModel, NumPy, SciPy, scikit-learn, etc.), Experience with SQL in cloud-based data stores required

US citizens and Green Card Holders and those authorized to work in the US are encouraged to apply. We are unable to sponsor H1b candidates at this time

Purpose of this hire: This role will be supporting lifetime value projections that report to the board. They will be doing statistical analysis on lifetime value for all Direct-to-Consumer clients’s products (subscription, advertising products etc.). They will work on churn related projects and sit between data science and finance/acquisition teams. This work will help understand the customer – information on what strategies will engage the customer, what ads/content appeal to them etc. The main purpose is to support acquisition and finance decisions – the acquisition team will be spending money on customer strategies and this role will help them understand the value of what they are trying to acquire (so not to spend more money than worth)

 

SENIOR DATA SCIENTIST

The Senior Data Scientist will be responsible for managing and executing high impact data science projects to support our Direct-to-Consumer business partners. These efforts will include but are not limited to 1) the projection of customer lifetime value across multiple media platforms; 2) hypothesis testing relative to customer engagement, segmentation, and churn; and 3) time series analyses of customer lifecycles and product features/development. Specifically, you will be responsible for the development and execution mathematical/statistical analyses as well as the implementation of operationalized algorithms and models.

The ideal technical skill set would include applied experience implementing methodologies such as survival analysis, RFM modelling via Pareto/NBD and other parametric distributions, time series analysis, and non-parametric modelling approaches to time-based predictions such as neural networks (CNN, LSTM, etc.).

 

You’ll need to be an innovative forward-thinker who will conduct end-to-end data science initiatives, work collaboratively with other data scientists as well as key business partners, and contribute directly to existing and emerging business strategies and goals. Communication and ability to thrive in a team environment are essential, as are strong technical skills, creativity and attention to detail, and experience conducting data science projects from use case definition to final product delivery.

 

Key Areas of Responsibility

  • Technical Responsibilities
    • Apply data mining techniques to cleanse and explore large, complex data sets in preparation for further analysis
    • Apply appropriate data reduction, feature selection, and feature engineering techniques
    • Develop, validate, and operationalize sound mathematical and statistical algorithms and models, with an eye toward deploying on large scale systems
    • Develop and implement hypothesis tests
    • Review, make enhancements to, and execute operationalized algorithms and models
    • Develop data products to communicate insights to business partners
    • Collaborate with data & technology teams to create repeatable processes and scalable data products

 

  • Project Scoping and Execution
    • Meet with business partners to flush out use cases and key requirements
    • Collaborate with data and technology teams to identify and source data sets required for analyses
    • Provide regular updates to and receive strategic direction from global data science team lead
    • Agree on project deliverable timelines with data science team & relevant data, technology, and business partners; manage project execution according to agreed timelines
    • Provide direction to senior/junior data scientists and review data science approaches, code, & deliverables
    • Prepare and communicate analytic insights to senior level management and business partners in clear business terms
    • Identify appropriate data science solutions as new data-centric business queries arise
    • Stay current with new data science methods, technologies, and industry trends

Preferred Qualifications

  • Master’s or PhD degree in a quantitative field (statistics, finance, econometrics, etc.)
  • Minimum of 5+ years proven business experience and technical expertise in data science
    • Applied experience related to customer lifetime value projection, including methodologies such as survival analysis; RFM(recency, frequency, monetary)/BTYD (buy til you die) frameworks; Pareto/NBD models and other parametric approaches/distributions; and non-parametric approaches such as neural networks (CNN, LSTM, etc.)
    • Experience with time-series analysis, time-based validation, hypothesis testing, clustering, regression, & classification
    • Experience cleansing and preparing large, complex datasets for analysis
    • Expertise in statistical programming languages such as R or Python (StatsModel, NumPy, SciPy, scikit-learn, etc.)
    • Experience with SQL in cloud-based data stores required; Amazon Web Services (RedShift, S3, EC2, EMR, etc.) and Apache Spark preferred
  • Professional-level expertise in developing, validating, and executing algorithms and models on large scale systems
  • Familiarity with data visualization applications, like Tableau or RShiny
  • Self-starter with strong analytical, critical thinking, and problem-solving skills
  • Excellent communication skills -- ability to present complex information in a concise and compelling manner
  • Prior media or direct-to-consumer industry experience preferred

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