Data Analyst c2c it jobs Philadelphia, PA

Role: Data Analyst
Location: Philadelphia, PA (4 days a week onsite)
Duration: 12+ Months

Must have:
SQL, Python, Tableau, Data bricks, AI/ML, Telecom experience

Requirements:
•       Experience & Domain Knowledge: 6+ years of experience in data
analytics or a related field, with a substantial portion in the
telecommunications industry preferably in the networking experienced in
data analysis/data scientist roles.
•       Data Analysis Skills: Exceptional analytical and problem-solving
skills. Advanced proficiency in SQL for querying large databases and
Python for data analysis (pandas, numpy, etc.) and scripting. You can
efficiently manipulate and analyze large datasets to extract meaningful
insights.
•       AI/ML & LLM Proficiency: Experience with machine learning or advanced
analytics techniques. Exposure to AI/ML frameworks (such as scikit-learn
or TensorFlow) and familiarity with Large Language Models (LLMs) or
natural language processing is a big plus – you’re comfortable exploring
new AI-driven approaches to glean insights from data (structured or
unstructured).
•       Data Visualization: Proficiency in creating clear and compelling
dashboards and visualizations using Tableau or Power BI (or similar
tools). You know how to tell a story with data, highlight key metrics,
and make complex data understandable to non-technical stakeholders.
•       Databricks & Big Data: Experience working with big data platforms like
Databricks (or Spark) to perform distributed data processing and
advanced analytics. Ability to optimize data workflows and handle
large-scale data (e.g., streaming data from telecom networks or
high-volume customer transaction data).
•       Detail-Oriented & Quality-Focused: Demonstrated commitment to data
quality and accuracy. Experience with data assurance practices, data
governance, or QA in analytics projects – you ensure the insights you
provide are rock-solid and reliable.
•       Strategic Mindset: Ability to see the big picture and align analysis
with business strategy. As a senior professional, you can prioritize
analysis that drives strategic decisions and not just produce reports.
You’re comfortable presenting to leadership and can translate data
findings into strategic recommendations.
•       Independent & Collaborative: Self-starter who can drive projects with
minimal guidance, and a team player who collaborates well across
departments. You can independently manage your workload and also work in
tandem with others – for example, pairing with a data engineer to
improve data pipelines or brainstorming with a product manager on what
metrics best define success for a new initiative.
•       Education: A Bachelor’s or Master’s degree in a relevant field (e.g.,
Data Science, Statistics, Computer Science, Engineering, or Business).
Equivalent hands-on experience and certifications in analytics/AI are
also considered.