What are the responsibilities and job description for the Senior Data Scientist position at Raas Infotek LLC?
Job Description: Senior Data Scientist
Experience: 12 Years
Job Title: Senior Data Scientist / Lead Data Scientist
Job Type: Full-Time
Job Summary
We are seeking an experienced Senior Data Scientist with 12 years of expertise in statistical modeling, machine learning, advanced analytics, and AI-driven solutions. The ideal candidate will have strong hands-on experience building predictive models, analyzing large datasets, deploying machine learning solutions, and translating business requirements into actionable insights.
Key Responsibilities
Design, develop, and deploy machine learning and statistical models for business problem-solving.
Perform exploratory data analysis (EDA), feature engineering, data cleaning, and data preprocessing.
Build predictive models using supervised and unsupervised learning techniques.
Develop and optimize algorithms for classification, regression, clustering, and forecasting.
Apply deep learning, Natural Language Processing (NLP), and Generative AI techniques where applicable.
Work with large datasets using Python, SQL, and distributed data processing frameworks.
Develop end-to-end machine learning pipelines and production-ready AI solutions.
Evaluate model performance, conduct A/B testing, and implement model monitoring.
Collaborate with data engineers, ML engineers, business analysts, and stakeholders.
Communicate analytical findings through dashboards, reports, and presentations.
Provide technical leadership, mentor junior data scientists, and establish best practices.
Required Technical Skills
Programming: Python, R, SQL
Machine Learning: Scikit-learn, XGBoost, TensorFlow, PyTorch
Statistics: Probability, hypothesis testing, regression, Bayesian methods
Data Processing: Pandas, NumPy, Spark, PySpark
Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
Cloud Platforms: AWS, Azure, or Google Cloud Platform
ML Operations: MLflow, Docker, Kubernetes, CI/CD, model deployment and monitoring
Advanced AI: Deep Learning, NLP, Generative AI, LLMs, and RAG
Data Platforms: Snowflake, Databricks, or similar platforms
Preferred Qualifications
Experience delivering enterprise-scale machine learning solutions.
Strong understanding of feature stores, model versioning, and ML lifecycle management.
Experience with large-scale data analysis and cloud-based AI platforms.
Excellent communication, problem-solving, and stakeholder management skills.
Experience leading data science projects from experimentation through production deployment.