Staff Software Development Engineer

You will be a key member of our department. This role requires a skilled professional with a strong background in Data Science and Machine Learning to analyze and interpret complex data, develop innovative solutions, and provide valuable insights to drive business growth. The successful candidate will have the opportunity to make a significant impact on our organization's data-driven decision-making processes.

• B.Tech / M.Tech in Computer Science, Statistics, Mathematics, Data Science, or a related field is required.
• 7+ years of experience in Data Science, Machine Learning, or Advanced Analytics roles, with a proven track record of success.
• Proficiency in Python and SQL, with hands-on experience in TensorFlow and/or PyTorch for model development.
• Experience with data engineering and cloud data platforms, including ETL/ELT pipelines and working with RDBMS and NoSQL databases on Azure, AWS, or GCP.
• Solid understanding of statistical modeling, probability theory, hypothesis testing, and data preprocessing techniques.
• Experience working with large-scale structured and unstructured datasets, and the ability to handle and process big data.
• Proficiency in data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn to present insights effectively.
• Familiarity with big data technologies like Spark and Hadoop is preferred.
• Strong problem-solving skills, analytical thinking, and the ability to communicate complex ideas to both technical and non-technical audiences.
• Experience in [industry domain – telecom, finance, healthcare, or embedded systems] is an advantage.

• Analyze large datasets to uncover trends, patterns, and insights, utilizing advanced statistical techniques.
• Develop, validate, and deploy machine learning models to support business objectives and make accurate predictions.
• Collaborate with engineering, product, and business teams to understand requirements and deliver tailored analytics solutions.
• Perform data preprocessing, cleaning, and feature engineering to ensure data quality and model accuracy.
• Design and implement experimental methodologies, including A/B testing and hypothesis testing, to validate assumptions.
• Visualize data insights through dashboards and reports, effectively communicating complex information to stakeholders.
• Automate data pipelines and workflows to streamline processes and improve efficiency.
• Work with structured and unstructured data sources, leveraging big data technologies to develop scalable analytics solutions.
• Stay updated with the latest advancements in Data Science, Machine Learning, and AI to enhance our analytics capabilities.
• Provide mentorship and guidance to junior team members, fostering a culture of knowledge sharing and continuous improvement.