Primary Responsibilities:

• Work with large, diverse datasets to deliver predictive and prescriptive analytics
• Develop innovative solutions using data modeling, machine learning, and statistical analysis
• Design, build, and evaluate predictive and prescriptive models and algorithms
• Use tools like SQL, Python, R, and Hadoop for data analysis and interpretation
• Solve complex problems using data-driven approaches
• Collaborate with cross-functional teams to align data science solutions with business goals
• Lead AI/ML project execution to deliver measurable business value
• Ensure data governance and maintain reusable platforms and tools
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Technical Skills
  • Programming Languages: Python, R, SQL
  • Machine Learning Tools: TensorFlow, PyTorch, scikit-learn
  • Big Data Technologies: Hadoop, Spark
  • Visualization Tools: Tableau, Power BI
  • Cloud Platforms: AWS, Azure, Google Cloud
  • Data Engineering: Talend, Data Bricks, Snowflake, Data Factory
  • Statistical Software: R, Python libraries
  • Version Control: Git

Preferred Qualifications:

• Master’s or PhD in Data Science, Computer Science, Statistics, or related field
• Certifications in data science or machine learning
• 7+ years of experience in a senior data science role with enterprise-scale impact
• Experience managing AI/ML projects end-to-end
• Solid communication skills for technical and non-technical audiences
• Demonstrated problem-solving and analytical thinking
• Business acumen to align data science with strategic goals
• Knowledge of data governance and quality standards