Lead Data Scientist; Work Location: Onsite Bengaluru, Karnataka, India; Annual salary: US$30 - 49 K/Year; Longterm (Duration)
Job Title: Lead Data Scientist
Work
Location: Onsite Bengaluru, Karnataka, India
Annual
salary: US$30 - 49 K/Year; Longterm (Duration)
Job Description:
Lead
Data Scientist – Healthcare Domain Specialist Location: Bangalore Company: RT
Global Info solutions Pvt Ltd (www.rgisol.com)
Client
Partner: Thrive Well Tech (https://www.thrivewelltech.com/)
Employment
Type: Full-Time
Industry:
Healthcare/AI/Analytics Domain Expertise: Predictive Analytics, Healthcare Data
About Us:
We
are a forward-thinking organization specializing in leveraging AI and data
science to solve real world problems specific to healthcare communities. Our
mission is to improve the quality of life for elderly residents through
innovative and predictive solutions. We are seeking an experienced Lead Data
Scientist with expertise in healthcare analytics to drive the development and
optimization of AIpowered predictive models. This role will focus on fall risk
prediction, chronic disease management, and clinical decision support systems,
working with EHR data, IoT sensor data, and real-time patient monitoring. As a
key leader in our data science team, you will define strategy, lead projects,
and collaborate with healthcare professionals, engineers, and product teams to
deploy scalable AI solutions.
Key Responsibilities:
- AI Model Development: Design, develop, and optimize predictive models for elderly fall risk assessment using advanced machine learning (ML) and deep learning techniques.
- Data Analysis: Work with healthcare-specific data (e.g., patient records, sensor data, clinical data) to uncover patterns and actionable insights.
- Domain Expertise Application: Leverage healthcare domain knowledge to ensure accuracy, reliability, and ethical use of models in predicting fall risks.
- Collaborate with Experts: Collaborate with clinicians, healthcare providers, and cross functional teams to align AI solutions with clinical workflows and patient care strategies.
- Data Engineering: Develop robust ETL pipelines to preprocess and integrate healthcare data from multiple sources, ensuring data quality and compliance.
- Evaluation & Optimization: Continuously evaluate model performance and refine algorithms to achieve high accuracy and generalizability.
- Compliance & Ethics: Ensure compliance with healthcare data regulations such as HIPAA, GDPR, and implement best practices for data privacy and security.
- Research & Innovation: Stay updated with the latest research in healthcare AI, predictive analytics, and elderly care solutions, integrating new techniques as applicable.
- Team Management: Guide all team members in technical and domain-specific problem solving, manage day to day task deliverables, evaluate individual’s performance and coach.
- Stakeholder Management: Present insights, models, and business impact assessments to senior leadership and healthcare stakeholders.
Required Skills & Qualifications
Education:
- Master's or PhD in Data Science, Computer Science, Statistics, Bioinformatics, or a related field. A strong academic background in healthcare is preferred.
Experience:
- 8 - 11 years of experience in data science, with at least 2 years in the healthcare domain. Prior experience in leading AI projects in healthcare startups, hospitals, or MedTech companies.
- Ability to work in cross-functional teams. o Ability to publish papers and research findings related to healthcare data science
Technical
Expertise:
- Proficiency in Python, R, or other programming languages used for ML and data analysis. Hands-on experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, Scikitlearn).
- Experience with time-series data, wearable/sensor data, or IoT data integration is a plus. Strong knowledge of statistics, probability, and feature engineering. o Familiarity with cloud platforms (AWS, Azure, GCP) and tools for scalable ML pipelines.
Healthcare
Domain Knowledge:
- Understanding of geriatric healthcare challenges, fall risks, and predictive care strategies. Familiarity with Electronic Health Records (EHR), wearable devices, and sensor data.
- Knowledge of healthcare data compliance (e.g., HIPAA, GDPR).
Soft
Skills:
- Strong analytical and problem-solving abilities.
- Excellent communication skills to present findings to non-technical stakeholders.
- A collaborative mindset to work with interdisciplinary teams. Preferred Qualifications
- Knowledge of biomechanics or human movement analysis.
- Experience with explainable AI (XAI) and interpretable ML models. What We Offer
- Opportunity to work on cutting-edge healthcare AI solutions that make a meaningful impact on elderly lives.
Offering:
- Competitive salary and benefits package.
- Flexible work environment, with options for hybrid work.
- Opportunities for professional growth and leadership.
- Collaborative and inclusive culture that values innovation and teamwork.
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