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Sr. Data Scientist / Machine Learning Engineer

Sr. Data Scientist / Machine Learning Engineer

C4 Technical ServicesNew York, NY, United States
1 day ago
Job type
  • Full-time
Job description

Sr. Data Scientist / Machine Learning Engineer

  • Start Date : December 1st or January (manager does not want anyone to start in mid-December due to the holidays)
  • Duration : 6 months with the opportunity to extend
  • Location : Washington, D.C., New York is preferred so a candidate may come onsite as needed, but remote is an option for the right candidate
  • Reason for opening : backfill
  • Interview Process : Three rounds of Zoom interviews

We are looking for a hands-on Data Scientist / Machine Learning Engineer with a strong technical background and deep experience in working with large datasets and advanced modeling techniques. This is an individual contributor role within a small team (3-4 people), focused on research, development, and implementation of machine learning algorithms to support various business initiatives.

Key Qualifications

  • Strong technical and programming skills; Python and SQL required, R is a plus.
  • Experience with advanced machine learning techniques , such as :

    • Causal ML

  • Forecasting
  • LSTM / Neural Networks
  • Transformers / LLaMA / other large language models
  • Not just basic models like propensity scoring
  • Solid experience (5+ years) working with large datasets and building production-level models.
  • Strong experience with hands-on coding ; this is not a strategic or managerial role.
  • Comfortable with independent research , staying current on machine learning trends and tools.
  • Should be able to evaluate and assemble libraries / codebases into usable solutions for the team.
  • Experience migrating platforms (e.g., to Databricks and Salesforce) and improving dashboards and visualizations.
  • Familiarity with Metalearners or willingness to research and work with them.
  • Must have a degree in a quantitative field : Data Science, Engineering, Statistics, Mathematics, etc.

    • MBAs or Business Analytics degrees are not a fit for this role.

  • Client / stakeholder management is not the primary focus .

    • Interview Tips

  • Ask candidates to walk through a machine learning algorithm end-to-end as applied to a real business problem.

    • How did they choose the algorithm?

  • Did they utilize forums, libraries, or research?
  • How did they evaluate its effectiveness (both technically and in business terms)?

    • How you'll make an impact :

  • You will build machine learning models to answer key business questions impacting strategy and marketing spend allocation
  • You will perform feature engineering and contribute to our feature store
  • You will lead dashboard development and lead development of enhanced visualization tools

    • What you'll do :

  • Build advanced machine learning models to inform marketing tactics (examples : adaptive clustering, reinforcement learning, regression modeling, price elasticity modeling etc.)
  • Execute sophisticated quantitative analyses and descriptive modeling to answer key business questions to shape business strategy.
  • Use enhanced python based graphical visualizations to deliver key insights to leadership.
  • Research and implement novel modeling techniques to solve complex business problems.
  • Develop analytics databases & lead development and maintenance of automated dashboards for AB experiment results.
  • Develop complex SQL queries combining data from a wide variety of sources in preparation of feature engineering or to perform analysis of business questions.
  • Measure incrementality of paid media campaigns using matched market testing.

    • What you'll need :

  • Bachelor's or Master's degree in data science, computer science, statistics, engineering, or related quantitative field.
  • Strong prior experience in data science, business & statistical analytics.
  • 7+ years of experience in related field.
  • Strong background in SQL & Python, R is a plus.
  • Experience in machine learning algorithms & libraries. Examples : CausalML / EconML, TensorFlow, PyTorch, Keras, sk-learn, seaborn, LSTM, RNN.
  • Experience with visualization tools.
  • Familiarity with Databricks platform is a plus.
  • Willingness to take initiative and to follow through on projects.
  • Excellent time management skills with the ability to prioritize and multi-task, and work under shifting deadlines in a fast-paced environment.
  • Must have legal right to work in the U.S.
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    Sr Machine Learning Engineer • New York, NY, United States