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Remote Opportunity Data Scientist with Healthcare Domain at Remote, Remote, USA
Email: [email protected]
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I have a  job
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Job Title:  
Data Scientist with Healthcare Domain

Location:  
Remote

1.

The requirement is hands-on
AL/ML model development. 

2.

Experience 8-10 years

Job Description:

We are seeking a highly
skilled AI/ML Engineer to join our dynamic team. As an AI/ML Engineer, you will
be responsible for analyzing underlying data sources and sets, identifying
relationships and correlations, building machine learning models, and
conducting thorough feasibility checks for patient scheduling solutions. You
will play a pivotal role in the design, development, testing, and deployment of
AI-powered solutions aimed at optimizing patient scheduling processes.

Responsibilities:

Analyze
Data: Collaborate with cross-functional teams to understand data requirements
and identify relevant data sources. Analyze and preprocess data to extract
valuable insights and ensure data quality.

Model
Development: Develop and implement machine learning models to address patient
scheduling challenges. Utilize advanced algorithms and techniques to optimize
scheduling processes and improve efficiency.

Hypothesis
Testing: Test hypotheses and validate assumptions through rigorous
experimentation and analysis. Conduct feasibility checks to assess the
viability and effectiveness of proposed solutions before deployment.

Solution
Design: Work closely with stakeholders to define requirements and translate
business objectives into technical specifications. Design scalable and robust
AI solutions tailored to meet specific client needs.

Evaluation
and Optimization: Evaluate model performance using appropriate metrics and
iterate on solutions to enhance performance and accuracy. Continuously optimize
algorithms and models to adapt to evolving business requirements.

Collaboration:
Collaborate with data engineers, software developers, and domain experts to integrate
AI/ML solutions into existing systems and workflows. Ensure seamless deployment
and integration of solutions within client environments.

Documentation
and Reporting: Document methodologies, findings, and outcomes in clear and
concise reports. Communicate results effectively to technical and non-technical
stakeholders, and provide actionable insights for decision-making.

Requirements:

Bachelor's
or Master's degree in Computer Science, Engineering, Statistics, or a related
field. Ph.D. preferred.

Proven
experience in data analysis, machine learning, and AI model development,
preferably in the healthcare domain.

Proficiency
in programming languages such as Python, R,  and familiarity with
python-notebooks for model development and libraries such as TensorFlow,
PyTorch, scikit-learn, etc.

Strong
understanding of statistical methods, data mining techniques, and predictive
modeling.

Experience
with data preprocessing, feature engineering, and model evaluation.

Excellent
problem-solving skills and the ability to think critically and analytically.

Strong
communication and interpersonal skills, with the ability to collaborate
effectively in a team environment.

Proven
track record of delivering high-quality solutions on time and within budget.

Knowledge
of healthcare standards and regulations (e.g., HIPAA) is a plus.

              Ability to adapt to a fast-paced,
dynamic work environment and learn new technologies quickly

Warm Regards

Shivi Sharma

Technical Recruiter

Tekshapers Inc

850 Stephenson Hwy, Suite 205, Troy, MI
48083

D: 248-306-8434
W: 248.565.4747 Ext. 134

Email:
 [email protected]

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ISO 9001:2008


Tekshapers
is an equal opportunity employer and will consider all applications without
regards to race, sex, age, color, religion, national origin, veteran status,
disability, sexual orientation, gender identity, genetic information or any
characteristic protected by law.

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Keywords: artificial intelligence machine learning rlang information technology Alabama Michigan
Remote Opportunity Data Scientist with Healthcare Domain
[email protected]
[email protected]
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Thu Apr 25 19:50:00 UTC 2024

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