Data Analysis Lead

Description

Location – Philadelphia, PA (onsite ) / West Chester, PA

Onsite Requirement – Hybrid 

Mandatory Skills SQL, Python, Tableau, Data bricks, AI/ML, Telecom experience – in networking area     
   

Optional Skills Power BI, Spark, ETL, ELT, Cloud Technologies

Must Have Skills –

• Skill 1 – 7 Yrs of Exp – SQL, Python,
• Skill 2 – 7 Yrs of Exp – , Tableau, Data bricks,
• Skill 3 – 5Yrs of Exp – AI/ML,

Lead II - Data Analysis This is an onsite role with minimum 4 days in office.

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.