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    Data Scientist - Hyderabad, India - Carrier

    Carrier
    Carrier background
    Full time
    Description

    Role Description

    :

    Data Scientist is crucial role in product development team at Carrier. As a Data Scientist you can dive deep into gigantic data from multiple sources and build smart data driven solutions that change the face of your BU. You will also work closely with cross-functional teams to develop and optimize AI models and contribute to the creation of innovative products, services, virtual assistants and chatbot solutions.

    Primary Skills/Expectations:

  • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.
  • Working knowledge in Python or R
  • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability.
  • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
  • Drive evangelization of data sciences across our division by communicating the use cases of advanced analytics
  • Track industry trend, drive data standards and best practices, and leverage latest industry technologies to increase efficiency of Data Science prototypes
  • Work with different Functional teams across the globe in identifying Business problems with impact analysis
  • Acquire Data from primary or secondary data sources available in structured and unstructured form
  • Perform Data modeling activities such as data cleansing, merging and enrichment etc.
  • Perform feature engineering through extracting meaningful features from measured and/or derived data
  • Proficient in SQL and experience with big data platforms like Hadoop, Spark, or similar technologies: Necessary for data manipulation and analysis.
  • Strong mathematical skills (e.g., statistics, algebra): Fundamental for data modeling and analysis.
  • Verifying data quality, and/or ensuring it via data cleaning.
  • Supervising the data acquisition process if more data is needed.
  • Defining validation strategies.
  • Defining the preprocessing or feature engineering to be done on a given dataset
    • Defining data augmentation pipelines
    • Building and implementing advanced machine learning models.
  • Training models and tuning their hyper parameters.
  • Analyzing the errors of the model and designing strategies to overcome them.
  • Deploying models to production.
  • Experience in processing and managing large data sets (TB scale) is preferred.
  • Experience:

  • 6-9 years of overall experience.
  • Qualifications:

  • B.E/B.Tech/MCA/M.Tech/M.Sc with Data Science/Statistics as major
  • Or additional diploma in Data Science from recognized university/college along with Degree in Engineering/Science(B.Tech/M.Tech/MSc./MCA)
  • Preferences:

  • Preference will be given to the person who participated in global Data Science challenges such as Kaggle to analyze large datasets.
  • Benefits:

  • We are committed to offering competitive benefits programs for all of our employees, and enhancing our programs when necessary.
  • Have peace of mind and body with our health insurance
  • Make yourself a priority with flexible schedules and leave Policy
  • Drive forward your career through professional development opportunities Achieve your personal goals with our Employee Assistance Program.
  • Our commitment to you :

    Our greatest assets are the expertise, creativity and passion of our employees. We strive to provide a great place to work that attracts, develops and retains the best talent, promotes employee engagement, fosters teamwork and ultimately drives innovation for the benefit of our customers. We strive to create an environment where you feel that you belong, with diversity and inclusion as the engine to growth and innovation. We develop and deploy best-in-class programs and practices, providing enriching career opportunities, listening to employee feedback and always challenging ourselves to do better. This is The Carrier Way.


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