Data Science Leader

7 days ago


Bengaluru, Karnataka, India Gameskraft Full time

About Gameskraft

We are building the world's most-loved online gaming ecosystem, one game at a time. Our short-term success lies in our commitment to focus on creating a safe, secure, and responsible gaming environment for everyone.

As a Senior Data Scientist at Gameskraft, you'll be actively involved in the daily development and execution of advanced analytics and machine learning solutions. You'll shape the data strategy, lead the team in deriving insights from large datasets, and ensure the successful deployment of data-driven solutions to achieve business goals.

The role requires strong expertise in machine learning, statistical modeling, and data analytics, with hands-on experience in algorithms such as regression, classification, clustering, and time series analysis. Proficient programming skills in languages like Python are also necessary, along with experience in libraries such as scikit-learn, TensorFlow, Keras, PyTorch, Pandas, NumPy, and Matplotlib for data manipulation, modeling, and visualization.

You will have the opportunity to collaborate on a diverse range of projects across multiple business units, gaining exposure to different aspects of the organization. This will allow you to broaden your expertise, learn from various domains, and understand how data science can drive value in different areas.

Data Strategy:

  • Develop and execute a comprehensive data strategy that aligns with the organization's objectives.
  • Identify and prioritize data science opportunities that drive business value.

Advanced Analytics and Machine Learning:

  • Oversee the design, development, and implementation of advanced analytics and machine learning models.
  • Ensure the team is utilizing state-of-the-art techniques and technologies to solve complex business problems.

Data Governance and Quality:

  • Establish and enforce data governance practices to ensure the accuracy and reliability of data used in analytics.
  • Collaborate with data engineering teams to ensure data quality and integrity.

Innovation:

  • Stay abreast of industry trends and emerging technologies in data science and analytics.
  • Foster a culture of innovation within the data science team.

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