Lead Data Scientist

TASC

full-time

Posted on: 9/24/2025

Origin: • 🇺🇸 United States • Missouri, New York

✨ AI Apply

💰 $138,000 - $221,000 per year

Senior

AWSAzureCloudGoogle Cloud PlatformHadoopNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Responsible for developing AI-driven innovative analytical solutions and identifying opportunities to support business and client needs in a quantitative and scalable manner, facilitating informed recommendations and decisions.
Activities include designing and deploying machine learning models, building intelligent AI/Gen AI systems, conducting performance analyses, and AI-powered data visualizations.
Lead complex initiatives and projects to derive insights and automation from AI models and systems to solve critical business questions
Translate client/stakeholder needs into AI/Gen AI-driven technical solutions in collaboration with internal and external partners and present findings and outcomes to clients/stakeholders
Identify rich data sources and oversee the integration, cleaning, and transformation of datasets to ensure consistency and readiness for AI applications
Deliver high-quality AI/Gen AI solutions and tools within agreed-upon timelines and budget parameters, and conducting post-implementation reviews
Guide others to develop sophisticated AI models and engineering solutions (e.g., intelligent agents, recommendation engines, prototypes) utilizing advanced machine learning, deep learning, and generative AI techniques
Serve as a technical coach for junior-level colleagues and develops technical talent via ongoing technical training, peer review, and mentorship

Strong experience delivering data science and machine learning solutions from concept to production, including model deployment, monitoring, and performance optimization.
Strong programming skills in Python (NumPy, Pandas, SciPy, scikit-learn) and experience with statistical modeling, predictive analytics, and data-driven experimentation.
Hands-on experience with deep learning frameworks (TensorFlow, PyTorch) and transformer-based architectures (e.g., BERT, GPT, ViTs, etc.)
Expertise in machine learning, deep learning, NLP, and MLOps practices (CI/CD for ML, model registry, feature stores).
Proficiency in data engineering concepts: building scalable pipelines for batch and streaming data (Spark, Hadoop) and working with SQL/relational databases.
Familiarity with cloud platforms (AWS, Azure, GCP) for data science workflows and model deployment.
Strong foundation in mathematics and statistics; advanced degree (Master’s or PhD) in Applied Mathematics, Statistics, Computer Science, or related field is preferred.
Skilled in data visualization and storytelling to translate complex analyses into actionable business insights.
Excellent communication and stakeholder management skills; ability to present findings to both technical and non-technical audiences.
Demonstrated leadership and mentoring experience, fostering growth in technical teams and guiding research or applied projects.
Ability to quickly learn new tools and technologies and adapt to evolving business needs.