DXFactor - Lead Data Scientist - Python/Big Data

Key Responsibilities : - Lead the end-to-end lifecycle of data science projects, including problem definition, data exploration, feature engineering, model development, validation, and deployment. - Architect and implement scalable and robust machine learning models and algorithms to address critical business problems. - Guide and mentor a team of data scientists and analysts, fostering their technical growth and ensuring high-quality deliverables. - Collaborate closely with product managers, engineers, and business stakeholders to understand their needs and translate them into actionable data science solutions. - Communicate complex analytical insights and findings to both technical and non-technical audiences in a clear and concise manner. - Drive innovation by researching and experimenting with new data science techniques, tools, and technologies. - Ensure the reproducibility and maintainability of data science workflows and models. - Contribute to the development of data science best practices and standards within the organization. - Evaluate and select appropriate data sources, tools, and methodologies for specific projects. - Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence. - Play a key role in shaping the data science roadmap and strategy for the Skills : - 7-9 years of hands-on experience in building and deploying machine learning models and statistical analyses in a business context. - Strong proficiency in Python and relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy). - Deep understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning) and their underlying principles. - Extensive experience with feature engineering, data cleaning, and data preprocessing techniques. - Solid understanding of statistical inference, hypothesis testing, and experimental design. - Experience with big data technologies and platforms (e.g., Spark, Hadoop, cloud-based data warehouses like Snowflake, BigQuery, Redshift) is highly desirable. - Experience with model deployment and monitoring tools (e.g., MLflow, Kubeflow, SageMaker). - Excellent communication and presentation skills with the ability to explain complex technical concepts to non-technical stakeholders. - Strong problem-solving and analytical skills with a proven ability to translate business problems into data science solutions. - Experience with version control systems (e.g., Git). - Bachelor's or Master's degree in Computer Science, or a related quantitative Skills : - Experience with specific industry domains relevant to our business (e.g., e-commerce, finance, healthcare). - Experience with natural language processing (NLP) or computer vision techniques. - Experience with time series analysis and forecasting. - Experience with A/B testing and causal inference. - Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data science services. - Experience with building and deploying real-time machine learning systems. - Leadership or mentorship experience within a data science team (ref:hirist.tech)

Location: gujarat, IN

Posted Date: 6/6/2025