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. O
• 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.