Data Scientist

Data Science and Analytics
Remote
November 26, 2024
Full Time

Job Overview

  • Date Posted
    November 26, 2024
  • Location
    Remote
  • Expiration date
    --
  • Gender
    Both
  • Career Level
    Associate
  • Experience
    2-5 Years

Job Description

Role Overview:
As a Data Scientist at Lead Panther, you will analyze complex datasets
to uncover trends, develop predictive models, and provide insights that
help shape strategic decisions. Your expertise in statistical analysis,
machine learning, and data visualization will play a critical role in
driving data-driven solutions.

Key Responsibilities:

1. Data Analysis & Exploration
– Gather, clean, and preprocess large datasets for analysis.
– Conduct exploratory data analysis (EDA) to understand data patterns
and generate initial insights.

2. Model Development
– Build and optimize machine learning models to solve complex business
problems.
– Implement and validate predictive models, ensuring their accuracy and
effectiveness.

3. Data Visualization & Communication
– Visualize data insights through dashboards, charts, and graphs for
clear, effective storytelling.
– Communicate findings and insights to both technical and non-technical
stakeholders.

4. Collaboration
– Work closely with cross-functional teams, including engineering,
product management, and business leaders, to integrate data science
solutions into business processes.
– Collaborate with data engineers to ensure efficient data flow and
model deployment.

5. Continuous Improvement
– Stay updated with the latest tools, techniques, and industry trends
in data science and machine learning.
– Experiment with new algorithms and tools to enhance data analysis
capabilities.

Qualifications:

– Education: Bachelor’s or Master’s degree in Data Science, Computer
Science, Statistics, Mathematics, or a related field.
– Experience: experience in data science, machine
learning, or a related field.
– Technical Skills:
– Proficiency in Python or R, with experience in libraries such as
pandas, NumPy, scikit-learn, TensorFlow, etc.
– Experience with SQL for data extraction and manipulation.
– Knowledge of data visualization tools like Tableau, Power BI, or
Matplotlib.
– Familiarity with cloud platforms (AWS, Google Cloud, Azure) is a
plus.
– Analytical Skills: Strong statistical and analytical skills with a
proven ability to solve complex problems.
– Communication Skills: Ability to clearly explain complex data
science concepts to a non-technical audience.

Preferred Qualifications:

– Experience with NLP, computer vision, or advanced machine learning
techniques.
– Background in big data tools and frameworks like Hadoop, Spark, or
Kafka.
– Experience with A/B testing and experimentation.

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