Senior Consultant - Data Science
- Arcadis
- 8 - 13 years
- Bengaluru
- 9 days ago
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Job Description
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.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Analytics - OtherRole: Data Science & Analytics - OtherEmployement Type: Full timeContact Details:
Company: ArcadisLocation(s): Bengaluru+ View Contact
Keyskills: Data Science Big Data Processing Software Development Data cleaning Data engineering Data mining cloud computing OCR
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