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About Hilabs:

Hilabs is a cutting-edge healthcare technology startup focused on leveraging data science, machine learning, and artificial intelligence to revolutionize the healthcare industry. Our mission is to develop data-driven solutions that improve patient outcomes, optimize clinical operations, and drive advancements in medical research. As we continue to scale, we are seeking an experienced Data Science / ML Manager to lead our data science and machine learning teams and help us shape the future of healthcare innovation.

Job Overview:

As the Data Science / Machine Learning Manager at Hilabs, you will play a key role in leading a talented team of data scientists and machine learning engineers to develop innovative solutions that solve complex problems in the healthcare domain. You will work closely with cross-functional teams, including product managers, engineers, and healthcare professionals, to drive impactful data-driven initiatives that improve patient care, enhance operational efficiency, and advance medical insights.

Your expertise in machine learning, healthcare data, and leadership will be essential as you guide the development of ML models, data pipelines, and analytics frameworks. In this role, you’ll have the opportunity to make a significant impact on the company's success and contribute to the transformation of the healthcare industry.

Key Responsibilities:

• Team Leadership & Mentorship:
  Lead and manage a team of data scientists, machine learning engineers, and analysts. Provide mentorship, foster professional growth, and promote a collaborative and innovative work environment.

• Strategy Development:
  Collaborate with senior leadership to define the data science and machine learning strategy, aligning it with Hilabs' mission and business goals. Identify key opportunities where data-driven solutions can create value.

• Machine Learning & AI Solutions:
  Oversee the development, deployment, and optimization of machine learning models for healthcare applications, such as predictive analytics, personalized treatment recommendations, clinical decision support systems, and more.

• Healthcare Data Expertise:
  Leverage your understanding of healthcare datasets (e.g., EHR, medical imaging, genomics, sensor data) to inform the design and development of models that address critical healthcare challenges.

• Cross-functional Collaboration:
  Work closely with product managers, engineers, healthcare experts, and other stakeholders to ensure that machine learning solutions align with product goals and are deployable in real-world healthcare settings.

• Data Infrastructure:
  Guide the team in building and maintaining scalable data pipelines, infrastructure, and data lakes to support machine learning workflows and ensure data quality, security, and compliance with healthcare regulations (e.g., HIPAA).

• Performance Monitoring & Optimization:
  Continuously monitor model performance, implement model improvements, and troubleshoot any issues related to model accuracy, scalability, or integration with other systems.

• Research & Innovation:
  Stay abreast of the latest advancements in machine learning, AI, and healthcare technology. Drive innovation within the team by exploring new algorithms, tools, and methodologies that can improve healthcare outcomes.

Qualifications:

• Education:
  Master’s or Ph.D. in Data Science, Computer Science, Mathematics, Statistics, or a related field.

• Experience:
  7+ years of experience in data science, machine learning, or AI, with at least 2-3 years in a leadership or managerial role. Experience working with healthcare data (e.g., EHR, medical imaging, clinical data) is highly preferred.

• Technical Skills:

  • Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
  • Expertise in programming languages such as Python, R, or Julia.
  • Experience with data engineering tools and big data technologies (e.g., Hadoop, Spark, SQL, NoSQL).
  • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud).

• Leadership & Communication:
  Strong leadership and team management skills. Ability to communicate complex technical concepts to non-technical stakeholders and collaborate effectively across departments.

• Healthcare Knowledge:
  Solid understanding of healthcare systems, clinical workflows, regulatory requirements (e.g., HIPAA), and the ethical considerations around healthcare data usage.

• Problem-Solving & Innovation:
  Demonstrated ability to think critically, solve complex problems, and drive innovation in machine learning and AI applications in healthcare.