Lead Data Scientist

Overview

On Site
Hybrid
Depends on Experience
Full Time

Skills

Data Science
Python

Job Details

Lead Data Scientist

NYC (Onsite or Hybrid)

W2

The Role

We are seeking a Lead Data Scientist to join our team and drive advanced data science solutions for one of our clients. This is a client-facing leadership role, blending deep technical expertise with the ability to advise stakeholders, shape data strategies, and guide teams to deliver high-impact outcomes.

You ll work on cutting-edge problems in data analytics, machine learning, and predictive modeling, helping the client unlock the value of their data and enhance decision-making capabilities.

Responsibilities:

    1. Partner with stakeholders to define data science opportunities, shape problem statements, and deliver impactful solutions.
    2. Lead end-to-end data science projects from exploration and modeling to deployment and performance monitoring.
    3. Mentor and guide a team of data scientists and data engineers; set best practices for modeling, experimentation, and validation.
    4. Design and implement predictive models, optimization frameworks, and machine learning algorithms tailored to complex business use cases.
    5. Develop and present compelling visualizations to convey complex data relationships through clear and insightful static graphics.
    6. Communicate complex technical concepts clearly to senior stakeholders, clients, and non-technical audiences.
    7. Collaborate with design and engineering teams to embed data science models into scalable digital products.
    8. Stay ahead of industry trends, research, and emerging technologies in AI/ML, with a focus on practical business applications.

Qualifications

    1. 8+ years of experience in data science, including at least 2 3 years in a lead/principal role.
    2. Strong background in applied machine learning, statistical modeling, and predictive analytics.
    3. Proficiency in Python (Pandas, NumPy, Scikit-learn, Matplotlib, PyTorch/TensorFlow) and SQL; experience with big data tools (Spark, Databricks) is a plus.
    4. Strong understanding of model deployment, MLOps practices, and productionizing ML solutions.
    5. Proven ability to create effective data visualizations for storytelling and decision support.
    6. Excellent client-facing skills, with the ability to communicate technical concepts and business impact.
    7. Master s or Ph.D. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.

Nice to Have

    1. Some fluency in blockchain and smart contract analytics.

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