Data Scientist

The Data Scientist role requires a highly analytical individual proficient in Python programming, database management, and data science methodologies. You'll focus on extracting insights from data, developing and implementing machine learning models, managing big data infrastructure, and supporting AI-driven product development. Key Responsibilities:Data Collection and Cleansing:Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making. Data Exploration and Visualization:Explore and visualize data using advanced techniques to uncover insights and trends. Statistical Analysis:Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modeling. Machine Learning and Deep Learning:Develop and implement machine learning and deep learning models to address business challenges. ML-Ops / AI-Ops:Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management. Big Data Management:Manage big data infrastructure and execute data engineering tasks for efficient data processing. Version Control and Collaboration:Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration. AI-Driven Product Development:Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives.


Required education
Bachelor's Degree

Preferred education
Master's Degree

Required technical and professional expertise

5+ years of expertise in Statistical Modeling and Machine Learning:Demonstrable deep understanding of statistics, machine learning, deep learning, neural networks, and NLP/NLU.

Strong programming skills in Python or R for data manipulation, analysis, and modeling.

Proficiency in machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, Keras, XGBoost, PyTorch).

Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and big data tools (e.g., Spark, Hadoop).

Experience with SQL and working with large, complex datasets.

Ability to interpret complex data patterns and translate them into actionable insights.

Preferred technical and professional experience

Knowledge of optimization techniques and algorithms for large-scale data problems.

Familiarity with MLOps principles and practices.

Familiarity with natural language processing (NLP), computer vision techniques, LLMs.