Data Scientist

Role: Data Scientist(Manufacturing)

Location: Durham, NC

Duration: 12+Months

Contract W2 only

Position is directly responsible for providing ongoing support for Manufacturing. This person facilitates engineering change projects and validation activities for sustaining production products. They will engage in discussions identifying, documenting and reporting quality issues and ensures that each issue is appropriately triaged for continual manufacturability.

Job Overview:

Quality Engineering is a fast paced, dynamic environment requiring decision making at the strategic and tactical levels. The job requires a highly motivated self-starter with an ability to work with minimal supervision in a team environment.

This role will serve as a resource to manufacturing to improve product quality, reliability, and process capability.

This role will facilitate teams in identifying, documenting, assessing, correcting and preventing quality issues using risk analysis and root cause analysis tools. This role will be responsible for quality planning and establishing and maintaining metrics to improve quality system processes, process capability, reliability and quality of products.

Accountabilities:

Develop and complete a data science strategy which is a part of the larger Digital Analytics Data Strategy aligned with Quality's goals

Understand business problems and design end-to-end data science use cases while providing business case analysis demonstrating how indicating value add

Quality Lead for complaint, installation failures, and Nonconformance data analytics

Provide Inputs to data science strategy which is a part of the larger Digital Analytics Data Strategy aligned with Quality's goals

Cross-functional Collaboration: Collaborate with other departments within Quality, the different business units and across the corporate enterprise to identify product and operational opportunities for data-driven improvements and efficiencies.

Stay up to date with emerging data and analytics technologies, recommending tools or platforms that can enhance the company's capabilities and information awareness.

Collaborate across the function to understand data, IT, and business constraints.

Collaborate with developers to implement and deploy scalable visualization solutions.

Establish best data operational practices and maintain all compliance requirements

Establish the monitoring of data science models in production.

Apply strong expertise in data science to design, prototype, and build the next-generation analytics engines and services.

Increase Data Literacy by guiding the organization about the business potential and strategy of artificial intelligence (AI)/data science.

Actively network on a regular basis with domain experts to better understand the business mechanics that generated the data.

Have a good understanding of end-to-end process

Lead and mentor a team of data scientists, fostering a culture of innovation and continuous learning

Qualifications:

Requires a minimum of a BS/MS degree in applied mathematics, engineering, or other relevant discipline. Graduate degree preferred.

Five-plus (5+) years of relevant work experience in data science.

Proven experience (5+ years) in a direct and/or matrixed leadership role in data and analytics.

Experience in a pharmaceutical, medical device or other regulated field a plus

Advanced statistical techniques and concepts and experience with applications.

Experience with a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

Experience presenting data and analysis to upper management.

Knowledge and skills:

Knowledge of statistical computer languages to manipulate data and draw insights from large data sets.

Ability to quickly develop extensive domain knowledge in various topics.

English working proficiency and communication skills (verbal and written).

Solid Working knowledge of Salesforce, PowerBI, Python, R, HQL, TensorFlow, PyTorch, SPARQL, D3JS and other dashboarding tools.

Knowledge of Pandas: Data Manipulation, Aggregation and Grouping, Visualization

Expert skills in LLM (Model Training, Deployment)

Knowledge of Prompt Engineering (GenAI)

Experience in Azure OpenAI and Databricks

Knowledgeable in Model validation and Evaluation techniques

Knowledge of data architecture, big data architectures, experience of building solutions on Azure, AWS, GCP, Multi-threaded data processing on CPU and GPU architectures.

Kindly share resume at call me at to discuss more.

Contract W2 only.