Data Scienctist Intern
- Build data models to address analytical and machine learning needs defined by the business
- Analyze large datasets to identify trends, patterns, and correlations that can provide actionable insights to Granite business stakeholders.
- Develop and implement statistical models, machine learning algorithms, and other data analysis techniques to solve complex business problems using Python, Pyspark, SQL server, Hadoop-based data platforms like Cloudera, and Cloud native platforms like GCP and AWS.
- Use data visualization tools like PowerBI to communicate findings and insights to non-technical stakeholders clearly and effectively.
- Work with business analysts and constituents to develop processes for acquiring, cleaning, and structuring data to ensure high-quality inputs for analysis.
- Work closely with business units and internal IT teams, including integrations with Granite’s data warehouse, internal applications like Salesforce, and other target systems to understand data needs and create pipelines via Python ETL scripts, GCP Feature Store or SQL server Proc for MuleSoft to gather relevant data from various internal and external sources.
- Clean, preprocess, and validate data integrity to ensure high-quality analysis.
- Design and develop ETL workflows to automate data collection and preparation processes using Spark, Python, Hive, Impala, and SQL Server Proc to ETL into GCP Vertex AI feature Store and data lakes in Cloudera or Salesforce.
- Collaboration and Communication with business stakeholders to expand Data science acceptance and adoption
- Collaborate with cross-functional teams, including business and IT teams, to define and prioritize data science projects.
- Present findings and recommendations to stakeholders, helping them make informed decisions based on data insights.
- Provide guidance and support to teammates as needed.
- Work with PMOs on Project Management using ADO
- Manage data science projects from concept to completion, ensuring they are delivered on time and within budget using Azure DevOps.
- Track project progress, report on milestones, and adjust project plans to meet changing business requirements by following proper Agile Methodology.
- Perform Research on innovative technologies in Data Science, Machine Learning, and AI for Granite 2.0 strategies
- Stay current with the latest advancements in data science, machine learning, and artificial intelligence, and apply new techniques and tools to improve data analysis processes.
- Focus on refining existing processes through continuous improvement, while fostering a culture of innovation by sharing insights and mentoring the team in adopting new techniques and tools
- Education:
- Pursuing Master’s Degree preferred in Information Systems, Data Science, Computer science, or a related field
- Technical Skills:
- Proficiency in programming languages such as Python or R, with experience in data manipulation and analysis.
- Knowledge of statistical analysis, machine learning algorithms, and data modeling techniques.
- Experience with data visualization tools (e.g., Tableau, Power BI, or similar).
- Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud computing platforms (e.g., AWS, GCP).
- Analytical and Problem-Solving Skills
- Ability to analyze complex datasets, identify patterns, and generate actionable insights.
- Strong problem-solving skills, with the ability to develop innovative solutions to business challenges.
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