Manager, Advisory (Multiple Positions), Philadelphia, PA

KPMG Careers; Philadelphia (Philadelphia County); Hybrid; USD 80,000 - 120,000; Full time

Job summary

An established industry player seeks a data scientist to leverage advanced statistical methods and machine learning to analyze structured and unstructured data. This role involves building recommendation engines, sentiment analyzers, and classifiers, while also driving client engagements in various domains such as product development and risk management. The ideal candidate will thrive in a dynamic environment, utilizing tools like Amazon EC2 and Hadoop to process large datasets. Join a forward-thinking company that values innovation and offers comprehensive benefits while making a significant impact in the field of data science.

Qualifications

• Master's or Bachelor's degree in Computer Science or related field required.
• 2+ years of experience in machine learning and data visualization.

Responsibilities

• Analyze and model structured data using advanced statistical methods.
• Drive client engagements focused on big data and advanced analytics.

Skills

Machine Learning

Data Visualization

Statistical Modeling

Data Mining

Natural Language Processing

Command-line Scripting

Data Structures

Algorithms

Education

Master's degree in Computer Science

Bachelor's degree in related fields

Tools

Amazon EC2

Hadoop

Spark

Tableau

Power BI

Microsoft SQL Server

Oracle

MapReduce

Pig

Hive

Job description

Analyze and model structured data using advanced statistical methods, and implement algorithms and software needed for analysis. Build recommendation engines, spam classifiers, sentiment analyzers, and classifiers for unstructured and semi-structured data. Cluster large amounts of user-generated content and process data in large-scale environments using Amazon EC2, Storm, Hadoop, and Spark. Perform machine learning, natural language processing, and statistical analysis methods, such as classification, collaborative filtering, association rules, sentiment analysis, topic modeling, time series analysis, regression, statistical inference, and validation methods.

Help drive client engagements focused on big data and advanced business analytics across diverse domains such as product development, marketing research, public policy, optimization, and risk management. Communicate results and educate others through reports and presentations. Perform explanatory data analyses, generate and test hypotheses, and analyze historical data to identify patterns.

Work Schedule

40 hours per week, M-F (9:00 a.m.–5:00 p.m.)

Job Requirements

1. Master's degree or foreign equivalent in Computer Science, Statistics, Data Science, Engineering, Mathematics, or a related field, with 2 years of related work experience; OR a Bachelor's degree or foreign equivalent in the same fields, with 5 years of progressive related work experience.
2. At least 2 years of experience with:
1. Command-line scripting, data structures, and algorithms
2. Working in Linux environment processing large data in a cloud environment
3. Utilizing machine learning, data visualization, statistical modeling, data mining, or information retrieval
4. Data extraction and processing using MapReduce, Pig, Hive, Microsoft SQL Server, or Oracle
5. Dashboarding software/platforms like Tableau or Power BI
3. Willingness to travel up to 40% domestically and internationally.
4. Telecommuting may be permitted within a commutable distance from the office, depending on business needs.
5. Employer accepts any suitable combination of education, training, or experience.

Application Process

Apply online at https://www.kpmguscareers.com/job-search and enter requisition number 123522 in the keyword search box for Experienced Professionals. For application assistance, contact [e-mail].

Must have legal right to work in the U.S. if offered employment. Comprehensive compensation and benefits are offered.

Additional Information

KPMG is an EOE/disability/veteran employer and maintains a drug-free workplace. No phone calls or agencies.