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    Data Scientist - Bengaluru, India - Talent Socio

    Talent Socio
    Talent Socio Bengaluru, India

    1 week ago

    Default job background
    Description

    Key Responsibilities :

    • Data Collection and Cleaning: Gather and process data from various sources, ensuring data quality and consistency.
    • Data Exploration: Explore and visualize data to understand patterns, trends, and anomalies.
    • Statistical Analysis: Apply statistical methods to extract meaningful insights from data, such as hypothesis testing, regression analysis, and clustering.
    • Machine Learning: Develop and implement machine learning models for predictive and prescriptive analytics. This includes feature engineering, model selection, and evaluation.
    • Data Mining: Discover hidden patterns and knowledge within data using techniques like association rule mining and anomaly detection.
    • Data Visualization: Create clear and informative data visualizations to communicate findings effectively to nontechnical stakeholders.
    • Model Deployment: Deploy machine learning models into production environments and monitor their performance.
    • A/B Testing: Design and analyze A/B tests to evaluate the impact of changes or interventions.
    • Domain Knowledge: Expertise in the healthcare domain and understand the context and nuances of the data.
    • Knowledge on clinical decision support, healthcare process optimization, disease surveillance, drug discovery and development, patient outcome improvements and brand performance.
    • Collaboration: Collaborate with crossfunctional teams, including engineers, business analysts, and domain experts, to solve complex problems and drive datadriven decisionmaking.

    Skills And Qualifications :

    • Data Analysis: Proficiency in data manipulation and analysis tools such as Python, R, or SQL.
    • Machine Learning: Strong knowledge of machine learning algorithms and frameworks (e.g., scikitlearn, TensorFlow, PyTorch).
    • Statistics : Solid understanding of statistical concepts and their application.
    • Data Visualization: Proficiency in data visualization libraries (e.g., Matplotlib, Seaborn, ) and tools (e.g., Apache Superset, Power BI).
    • Big Data Tools: Familiarity with big data technologies like Hadoop and Spark is a plus.
    • Programming: Ability to write code for data analysis and modeling in cloud environment

    Database Knowledge:
    Understanding of relational databases and NoSQL databases.

    • Domain Expertise: Understanding of healthcare systems, medical terminology, and clinical processes is essential.
    • Communication: Strong communication skills to convey complex findings to nontechnical stakeholders.
    • Problem Solving: Analytical and critical thinking skills to approach and solve complex business problems.
    • Interdisciplinary Collaboration: Collaborate with healthcare providers, clinicians, data engineers, and researchers to address healthcare challenges and drive datadriven solutions.
    )
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