Data Scientist ( Developer )

Job Description

Candidate Skill: Technical Skills - Python | R | AI/ML | TensorFlow | Keras | PyTorch | Scikit-learn | SQL | Data Visualization | Deep Learning | Cloud Platforms (AWS, Azure, GCP) | Docker | Kubernetes We are looking for a talented Data Scientist (Developer) to join our team in Hyderabad. The ideal candidate will have a strong background in AI/ML, with hands-on experience in developing data-driven solutions. You will collaborate with cross-functional teams to build and deploy machine learning models that solve real-world problems, improve business processes, and drive decision-making. Key Responsibilities: Develop machine learning models and algorithms to extract insights and make data-driven decisions. Implement advanced data analytics and machine learning models using AI/ML techniques. Work closely with product and business teams to understand business requirements and translate them into machine learning solutions. Collaborate with data engineers to collect, clean, and process large datasets. Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in data. Design and implement data pipelines to automate the processing and analysis of data. Test and validate models to ensure they perform optimally in production. Optimize existing models for improved performance and scalability. Communicate results to non-technical stakeholders through clear visualizations and reports. Stay up-to-date with the latest developments in the field of AI/ML. Required Skills and Qualifications: 4-7 years of experience in Data Science, with a minimum of 3 years in AI/ML development. Proficiency in programming languages such as Python and R for building machine learning models. Strong understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning. Hands-on experience with AI/ML frameworks such as TensorFlow, Keras, PyTorch, or Scikit-learn. Experience with data wrangling, feature engineering, and model evaluation techniques. Familiarity with data visualization tools such as Matplotlib, Seaborn, or Tableau. Strong knowledge of SQL for querying large datasets. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for model deployment and scaling. Experience with Docker and Kubernetes for model deployment is a plus. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication skills to present technical concepts to non-technical stakeholders.