Senior Consultant Data Science

Qualification & Experience:

Minimum of 8 years of experience as a Data Scientist/Engineer with demonstrated expertise in data engineering and cloud computing technologies

Technical Responsibilities

• Excellent proficiency in Python, with a strong focus on developing advanced skills
• Extensive exposure to NLP and image processing concepts
• Proficient in version control systems like Git
• In-depth understanding of Azure deployments
• Expertise in OCR, ML model training, and transfer learning
• Experience working with unstructured data formats such as PDFs, DOCX, and images
• Strong familiarity with data science best practices and the ML lifecycle
• Strong experience with data pipeline development, ETL processes, and data engineering tools such as Apache Airflow, PySpark, or Databricks
• Familiarity with cloud computing platforms like Azure, AWS, or GCP, including services like Azure Data Factory, S3, Lambda, and BigQuery
• Tool Exposure: Advanced understanding and hands-on experience with Git, Azure, Python, R programming and data engineering tools such as Snowflake, Databricks, or PySpark
• Data mining, cleaning and engineering: Leading the identification and merging of relevant data sources, ensuring data quality, and resolving data inconsistencies
• Cloud Solutions Architecture: Designing and deploying scalable data engineering workflows on cloud platforms such as Azure, AWS, or GCP
• Data Analysis: Executing complex analyses against business requirements using appropriate tools and technologies
• Software Development: Leading the development of reusable, version-controlled code under minimal supervision
• Big Data Processing: Developing solutions to handle large-scale data processing using tools like Hadoop, Spark, or Databricks

Principal Duties & Key Responsibilities

• Leading data extraction from multiple sources, including PDFs, images, databases, and APIs
• Driving optical character recognition (OCR) processes to digitize data from images
• Applying advanced natural language processing (NLP) techniques to understand complex data
• Developing and implementing highly accurate statistical models and data engineering pipelines to support critical business decisions and continuously monitor their performance
• Designing and managing scalable cloud-based data architectures using Azure, AWS, or GCP services
• Collaborating closely with business domain experts to identify and drive key business value drivers
• Documenting model design choices, algorithm selection processes, and dependencies
• Effectively collaborating in cross-functional teams within the CoE and across the organization
• Proactively seeking opportunities to contribute beyond assigned tasks
• Required Competencies:
• Exceptional communication and interpersonal skills
• Proficiency in Microsoft Office 365 applications
• Ability to work independently, demonstrate initiative, and provide strategic guidance
• Strong networking, communication, and people skills
• Outstanding organizational skills with the ability to work independently and as part of a team
• Excellent technical writing skills
• Effective problem-solving abilities
• Flexibility and adaptability to work flexible hours as required

Key competencies / Values:

• Client Focus: Tailoring skills and understanding client needs to deliver exceptional results
• Excellence: Striving for excellence defined by clients, delivering high-quality work
• Trust: Building and retaining trust with clients, colleagues, and partners
• Teamwork: Collaborating effectively to achieve collective success
• Responsibility: Taking ownership of performance and safety, ensuring accountability
• People: Creating an inclusive environment