Position: Senior Data Scientist
Job Summary
We are seeking an experienced and highly analytical Senior Data Scientist to join our team. The ideal candidate will leverage advanced statistical methods, machine learning, and data-driven insights to solve complex business problems. You will work closely with cross-functional teams to develop predictive models, optimize business processes, and drive strategic decision-making through data.
Key Responsibilities
- Design, develop, and deploy machine learning models and predictive analytics solutions.
- Analyze large, complex datasets to identify trends, patterns, and actionable insights.
- Collaborate with product, engineering, and business stakeholders to define data-driven solutions.
- Build and maintain scalable data pipelines and analytical workflows.
- Develop and evaluate statistical models using appropriate validation techniques.
- Communicate technical findings and recommendations to both technical and non-technical audiences.
- Mentor junior data scientists and provide technical leadership on data science initiatives.
- Stay current with the latest advancements in machine learning, artificial intelligence, and data science.
- Ensure data quality, governance, and compliance with organizational standards.
- Support A/B testing, experimentation, and performance measurement initiatives.
Required Qualifications
Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. 5–8+ years of experience in data science, machine learning, or advanced analytics.
Strong programming skills in Python and/or R.
Experience with SQL and large-scale data processing.
Hands-on experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
Strong understanding of statistics, probability, and experimental design.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Familiarity with big data technologies such as Spark, Hadoop, or Databricks.
Excellent problem-solving, communication, and stakeholder management skills.
Preferred Qualifications
Experience with MLOps and model deployment. Knowledge of Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Experience with Docker, Kubernetes, and CI/CD pipelines.
Familiarity with BI tools such as Tableau or Power BI.
Experience working in Agile development environments.
Key Skills
Machine Learning Deep Learning
Statistical Modeling
Python, R, SQL
Data Visualization
Feature Engineering
Predictive Analytics
Data Engineering Concepts
Cloud Computing
MLOps
Problem Solving
Leadership and Mentoring
Business Communication
Success Metrics
Delivery of high-impact machine learning solutions. Improvement in model accuracy and business KPIs.
Timely completion of analytics projects.
Effective collaboration with cross-functional teams.
Contribution to innovation and continuous improvement in data science practices.
