Job Title: Data Science Lead Specialist Engineer
Location: Delaware, Delaware
Experience Required: 12+ Years
Employment Type: Contract
Interview Type: In-Person or Webcam

We are seeking a highly experienced Data Science Lead Specialist Engineer with strong expertise in advanced analytics, machine learning, statistical modeling, and data engineering. The ideal candidate will be responsible for driving end-to-end data science initiatives, leading technical teams, collaborating with business stakeholders, and developing scalable AI and ML solutions that solve complex business problems.

• Lead data science strategy, architecture, design, and implementation across multiple business units.

• Work closely with stakeholders to identify business opportunities, gather requirements, and translate them into analytics and ML models.

• Develop predictive and prescriptive models leveraging machine learning, deep learning, NLP, and other advanced techniques.

• Perform large-scale data exploration, data mining, feature engineering, and model optimization.

• Design and implement scalable pipelines for model training, deployment, and monitoring in production environments.

• Lead a team of data scientists, analysts, and ML engineers, providing technical mentorship and guidance.

• Evaluate new technologies, tools, and frameworks to improve model performance and efficiency.

• Present actionable insights and deliver executive-level data-driven recommendations.

• Ensure data governance, quality assurance, security, and compliance best practices.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.

• 12+ years of experience in Data Science, Machine Learning, AI engineering, or related areas.

• Strong programming skills in Python, R, Scala, and SQL.

• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, Spark MLlib.

• Strong experience with cloud platforms such as AWS, Azure, or Google Cloud, including ML Ops capabilities.

• Proven experience designing and deploying production-grade machine learning solutions.

• Expertise in statistical modeling, predictive analytics, optimization, deep learning, and NLP techniques.

• Experience working with big data technologies such as Spark, Hadoop, Hive, Kafka, Databricks.

• Excellent communication skills with ability to clearly present complex analytics to non-technical stakeholders.

• Leadership experience managing teams and driving enterprise-wide initiatives.

• PhD in a quantitative discipline or equivalent advanced research background.

• Experience in data visualization tools such as Power BI, Tableau, or Looker.

• Experience with DevOps and ML Ops tools such as Docker, Kubernetes, Airflow, MLflow, Kubeflow.

• Experience in Generative AI, LLM fine-tuning, and vector databases.

• Experience working in regulated industries such as Finance, Healthcare, or Insurance.

• Ability to architect large-scale data science platforms and automation frameworks.