DATA SCIENTIST

4P Consulting Inc.; Forest Park (GA); On-site; USD 100,000 - 130,000; Full time

Job summary

A leading consulting firm is seeking a Data Scientist to leverage data insights for decision-making. This role focuses on data analysis, predictive modeling, and collaboration across teams. With responsibilities including machine learning and data visualization, candidates should possess 5 to 10 years of relevant experience and strong problem-solving skills.

Qualifications

• 5 to 10 years of experience in data science, including machine learning and statistical analysis.
• Proficiency in Python, R, or Julia and data visualization tools like Tableau and Power BI.
• Solid understanding of databases and SQL for data manipulation.

Responsibilities

• Leverage data to uncover insights and create predictive models.
• Develop and deploy machine learning models for predictions.
• Collaborate with cross-functional teams to align initiatives with goals.

Skills

Data Analysis

Machine Learning

Problem Solving

Data Visualization

Hypothesis Testing

Feature Engineering

Data Ethics

Collaboration

Education

Bachelor's degree in a quantitative field

Master's or Ph.D. is a plus

Tools

Python

R

SQL

Tableau

Power BI

Hadoop

Spark

Job description

HI,

Hope you're doing well

This is pankaj from 4P Consulting Please see below job description

Please share your resume if you're interested and have 5-10 years of experience submission on W2 basis only NO C2C

• A Data Scientist with 5 to 10 years of
  experience is responsible for leveraging
  data to uncover insights, create predictive
  models, and drive data-driven decision-
  making within an organization.
• This role
  involves advanced analytics, machine
  learning, and strong problem-solving skills
  to extract actionable information from
  large datasets. Key Responsibilities: Data
  Analysis: Collect, clean, and analyze
  complex datasets to identify trends,
  patterns, and actionable insights.
• Use
  statistical techniques to uncover
  meaningful information from data.
  Predictive Modeling: Develop and deploy
  machine learning models to predict future
  trends, behaviors, and outcomes. Apply
  regression analysis, clustering,
  classification, and other modeling
  techniques.
• Data Visualization: Create
  compelling data visualizations to
  communicate findings effectively to both
  technical and non-technical stakeholders
  using tools like Tableau, Power BI, or
  Python libraries. Hypothesis Testing:
  Formulate and test hypotheses, providing
  statistical validation for business
  decisions and recommendations.
• Feature
  Engineering: Engineer and select relevant
  features for machine learning models,
• enhancing their predictive power.
  Algorithm Development: Build and fine-
  tune machine learning algorithms, such
  as decision trees, random forests, neural
  networks, and more, depending on the
  specific problem.
• Data Integration:
  Collaborate with IT and database
  administrators to integrate and access
  data from various sources and data
  warehouses. Model Deployment: Deploy
  machine learning models in production
  environments to support real-time
  decision-making. A/B Testing: Design and
  analyze A/B tests to measure the impact
  of changes and improvements. Data
  Ethics:
• Ensure ethical data practices,
  including privacy and compliance with
  data protection regulations. Cross-
  functional Collaboration: Collaborate with
  cross-functional teams, including
  engineers, business analysts, and domain
  experts, to understand business
  requirements and align data science
  initiatives with organizational goals.
  Mentorship:
• Provide guidance and
  mentorship to junior data scientists and
  analysts, fostering their professional
  growth. Continuous Learning: Stay
  updated on the latest data science tools,
  techniques, and trends through ongoing
  professional development. Qualifications:
  Bachelor's degree in a quantitative field
  (e.g., Computer Science, Statistics,
  Mathematics, Engineering); a Master's or
  Ph.D. is a plus.
• 5 to 10 years of experience
  in data science, including machine
  learning and statistical analysis.
  Proficiency in data analysis tools and
  programming languages such as Python,
  R, or Julia. Strong knowledge of machine
  learning algorithms and their applications.
  Experience with data visualization toolslike Tableau, Power BI, or data
  visualization libraries in Python (e.g.,
  Matplotlib, Seaborn). Solid understanding
  of databases and data manipulation using
  SQL. Excellent problem-solving and
  critical thinking skills. Strong
  communication skills to convey complex
  findings and insights to both technical and
  non-technical stakeholders. Familiarity
  with big data technologies and distributed
  computing frameworks is a plus (e.g.,
  Hadoop, Spark). Knowledge of data
  ethics, privacy, and compliance
  considerations.
• A Data Scientist with 5 to
  10 years of experience is a critical asset to
  an organization, capable of transforming
  data into actionable insights, building
  predictive models, and driving data-driven
  decision-making. This role requires a
  strong foundation in data science
  techniques, programming, and advanced
  analytics, as well as the ability to
  collaborate with various teams and
  mentor junior staff.

Thanks and Regards

Sr. Talent Acquisition Specialist

Pankaj Mishra

[e-mail]

[phone]