Data Science Intern

Key Skills

Advanced Analytics, Apache Hadoop, Big Data Technology, Data Analysis, Data Visualization, Deep Learning, Effective communication skills, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, SPARK Programming, SQL, Statistical modeling, TensorFlow

Job Description

As a Data Science Intern, you will be analyzing and extracting valuable insights from massive data pipelines. This is an immersive, hands-on position where you will be actively involved in writing code, collaborating with cross-functional teams, and presenting your findings. With a mentor, you will contribute to complex projects that challenge your analytical and technical abilities and help develop your skills as a data scientist.

Duration – June 12, 2023, through August 25, 2023

Responsibilities

• Utilize your analytical and statistical skills to perform end-to-end analyses on complex data sets, identifying, analyzing, and interpreting patterns and trends. Translate findings into actionable insights that drive business impact.
• Collaborate with cross-functional teams to collect and combine data from multiple sources and apply advanced analytics, machine learning, or NLP techniques to deliver on projects that address complex business challenges.
• Analyze and visualize data outputs to effectively communicate insights to stakeholders enabling them to make data-driven decisions.

Minimum Qualifications

• Currently pursuing a Bachelors/MS in Data Science, Statistics, or a highly quantitative field (e.g. Computer Science, Physics, Engineering).
• Must have at least one semester/term/quarter of school left to complete after the end of the internship.
• Good command in programming skills like Python/SQL.
• Understanding of statistical and machine learning concepts.

• Desire to pursue challenging questions through extensive operational and data analysis.
• Strong written and verbal communication skills.

Preferred Qualifications

• Prior experience with big data technologies such as Hadoop or Spark.
• Experience using deep learning libraries such as TensorFlow or PyTorch.