Data Scientist 2

BLOC Resources is seeking a highly skilled and motivated Data Scientist 2 to support advanced data analytics initiatives for our client located in Atlanta, Georgia. This role will play a key part in transforming large and complex datasets into actionable insights that support strategic business decisions.

The ideal candidate will have 5–10 years of professional experience in data science, machine learning, and statistical analysis, along with a strong technical background in programming and data modeling. This individual will collaborate with cross-functional teams including business stakeholders, engineers, analysts, and IT professionals to develop predictive models, optimize processes, and improve overall business performance through data-driven solutions.

This position requires strong analytical thinking, technical expertise, and the ability to effectively communicate complex data findings to both technical and non-technical audiences.

Key Responsibilities

Advanced Data Analysis

- Collect, process, and analyze large, complex datasets from multiple internal and external data sources.

- Perform exploratory data analysis to identify trends, correlations, and anomalies.

- Apply statistical methods to interpret data and generate meaningful insights that support operational and strategic decision-making.

- Ensure data accuracy, integrity, and consistency throughout the analytics lifecycle.

Machine Learning & Predictive Modeling

- Design, develop, and implement machine learning models to predict trends, behaviors, and outcomes.

- Utilize techniques such as regression analysis, classification models, clustering algorithms, and time-series forecasting.

- Develop and optimize algorithms including decision trees, random forests, gradient boosting models, and neural networks.

- Evaluate model performance using validation techniques and performance metrics.

- Continuously improve models through feature optimization and retraining.

Data Visualization & Reporting

- Create dashboards, visual reports, and interactive data visualizations that clearly communicate key findings.

- Translate complex analytical results into understandable insights for business stakeholders.

- Utilize visualization tools such as:

- Power BI

- Tableau

- Python libraries (Matplotlib, Seaborn, Plotly)

Hypothesis Testing & Experimentation

- Design and conduct experiments to evaluate business strategies and operational changes.

- Perform statistical hypothesis testing to validate assumptions and identify causal relationships.

- Develop and analyze A/B tests to measure the effectiveness of process improvements or product changes.

Feature Engineering & Data Preparation

- Identify and develop relevant features that enhance predictive accuracy and model performance.

- Perform data transformation, normalization, and cleaning to prepare datasets for modeling.

- Work with structured and unstructured data sources to extract meaningful features.

Data Integration & Pipeline Collaboration

- Partner with data engineers, IT teams, and database administrators to access and integrate data from multiple platforms and databases.

- Assist in building scalable data pipelines and workflows that support ongoing analytics initiatives.

- Ensure efficient data retrieval and performance optimization.

Model Deployment & Monitoring

- Deploy machine learning models into production environments.

- Develop monitoring systems to track model performance and accuracy over time.

- Update and retrain models as new data becomes available or business needs evolve.

Data Governance & Ethics

- Follow best practices for ethical data usage and privacy protection.

- Ensure compliance with data security policies and regulatory standards.

- Promote responsible data management practices throughout the organization.

Cross-Functional Collaboration

- Work closely with business leaders, analysts, product teams, and engineers to understand business challenges.

- Translate business requirements into technical data science solutions.

- Present insights and recommendations to stakeholders and leadership teams.

Mentorship & Team Support

- Provide guidance and technical mentorship to junior data scientists, analysts, and team members.

- Assist with code reviews, model validation, and knowledge sharing across the analytics team.

- Contribute to building a collaborative and innovative data science environment.

Continuous Improvement & Innovation

- Stay up to date on emerging technologies, tools, and methodologies in data science and machine learning.

- Identify opportunities to improve analytics capabilities and introduce new techniques to enhance business insights.

Required Qualifications

Education

- Bachelor’s degree in a quantitative or technical field such as:

- Computer Science

- Data Science

- Statistics

- Mathematics

- Engineering

- Master’s degree or Ph.D. preferred

Professional Experience

- 5–10 years of professional experience in data science, analytics, or machine learning

- Experience working with large datasets and advanced statistical analysis

- Proven experience developing predictive models and deploying machine learning solutions

Technical Skills

Candidates should demonstrate strong proficiency in the following:

Programming Languages

- Python

- R

- Julia (preferred but not required)

Data Analysis & Machine Learning

- Machine learning algorithms and statistical modeling

- Predictive analytics

- Feature engineering

- Model evaluation and validation

Data Visualization

- Tableau

- Power BI

- Python visualization libraries such as Matplotlib, Seaborn, or Plotly

Database & Data Management

- Strong SQL skills

- Experience with relational and non-relational databases

- Data manipulation and transformation techniques

Preferred Skills

The following experience is considered a plus:

- Experience with big data technologies such as Hadoop or Spark

- Experience with distributed computing frameworks

- Familiarity with cloud platforms (AWS, Azure, or Google Cloud)

- Experience working in enterprise data environments

- Knowledge of data governance, compliance, and privacy regulations

Professional Skills

The successful candidate will demonstrate:

- Strong analytical and problem-solving capabilities

- Ability to think critically and interpret complex datasets

- Excellent written and verbal communication skills

- Ability to explain complex technical concepts to non-technical audiences

- Strong attention to detail and commitment to data quality

- Ability to manage multiple projects and priorities in a fast-paced environment

- Collaborative mindset with strong teamwork abilities

BLOC Resources

Location: 30 Ivan Allen Jr Blvd NW, Atlanta, GA 30308 Pay Rate: $44.00-$48.00 per hour Position Type: Contract Opportunity Work Environment: Onsite / Hybrid (based on client needs)

Position Overview

BLOC Resources is seeking a highly skilled and motivated Data Scientist 2 to support advanced data analytics initiatives for our client located in Atlanta, Georgia. This role will play a key part in transforming large and complex datasets into actionable insights that support strategic business decisions.

The ideal candidate will have 5–10 years of professional experience in data science, machine learning, and statistical analysis, along with a strong technical background in programming and data modeling. This individual will collaborate with cross-functional teams including business stakeholders, engineers, analysts, and IT professionals to develop predictive models, optimize processes, and improve overall business performance through data-driven solutions.

This position requires strong analytical thinking, technical expertise, and the ability to effectively communicate complex data findings to both technical and non-technical audiences.

Key Responsibilities

Advanced Data Analysis

- Collect, process, and analyze large, complex datasets from multiple internal and external data sources.

- Perform exploratory data analysis to identify trends, correlations, and anomalies.

- Apply statistical methods to interpret data and generate meaningful insights that support operational and strategic decision-making.

- Ensure data accuracy, integrity, and consistency throughout the analytics lifecycle.

Machine Learning & Predictive Modeling

- Design, develop, and implement machine learning models to predict trends, behaviors, and outcomes.

- Utilize techniques such as regression analysis, classification models, clustering algorithms, and time-series forecasting.

- Develop and optimize algorithms including decision trees, random forests, gradient boosting models, and neural networks.

- Evaluate model performance using validation techniques and performance metrics.

- Continuously improve models through feature optimization and retraining.

Data Visualization & Reporting

- Create dashboards, visual reports, and interactive data visualizations that clearly communicate key findings.

- Translate complex analytical results into understandable insights for business stakeholders.

- Utilize visualization tools such as:

- Power BI

- Tableau

- Python libraries (Matplotlib, Seaborn, Plotly)

Hypothesis Testing & Experimentation

- Design and conduct experiments to evaluate business strategies and operational changes.

- Perform statistical hypothesis testing to validate assumptions and identify causal relationships.

- Develop and analyze A/B tests to measure the effectiveness of process improvements or product changes.

Feature Engineering & Data Preparation

- Identify and develop relevant features that enhance predictive accuracy and model performance.

- Perform data transformation, normalization, and cleaning to prepare datasets for modeling.

- Work with structured and unstructured data sources to extract meaningful features.

Data Integration & Pipeline Collaboration

- Partner with data engineers, IT teams, and database administrators to access and integrate data from multiple platforms and databases.

- Assist in building scalable data pipelines and workflows that support ongoing analytics initiatives.

- Ensure efficient data retrieval and performance optimization.

Model Deployment & Monitoring

- Deploy machine learning models into production environments.

- Develop monitoring systems to track model performance and accuracy over time.

- Update and retrain models as new data becomes available or business needs evolve.

Data Governance & Ethics

- Follow best practices for ethical data usage and privacy protection.

- Ensure compliance with data security policies and regulatory standards.

- Promote responsible data management practices throughout the organization.

Cross-Functional Collaboration

- Work closely with business leaders, analysts, product teams, and engineers to understand business challenges.

- Translate business requirements into technical data science solutions.

- Present insights and recommendations to stakeholders and leadership teams.

Mentorship & Team Support

- Provide guidance and technical mentorship to junior data scientists, analysts, and team members.

- Assist with code reviews, model validation, and knowledge sharing across the analytics team.

- Contribute to building a collaborative and innovative data science environment.

Continuous Improvement & Innovation

- Stay up to date on emerging technologies, tools, and methodologies in data science and machine learning.

- Identify opportunities to improve analytics capabilities and introduce new techniques to enhance business insights.

Required Qualifications

Education

- Bachelor’s degree in a quantitative or technical field such as:

- Computer Science

- Data Science

- Statistics

- Mathematics

- Engineering

- Master’s degree or Ph.D. preferred

Professional Experience

- 5–10 years of professional experience in data science, analytics, or machine learning

- Experience working with large datasets and advanced statistical analysis

- Proven experience developing predictive models and deploying machine learning solutions

Technical Skills

Candidates should demonstrate strong proficiency in the following:

Programming Languages

- Python

- R

- Julia (preferred but not required)

Data Analysis & Machine Learning

- Machine learning algorithms and statistical modeling

- Predictive analytics

- Feature engineering

- Model evaluation and validation

Data Visualization

- Tableau

- Power BI

- Python visualization libraries such as Matplotlib, Seaborn, or Plotly

Database & Data Management

- Strong SQL skills

- Experience with relational and non-relational databases

- Data manipulation and transformation techniques

Preferred Skills

The following experience is considered a plus:

- Experience with big data technologies such as Hadoop or Spark

- Experience with distributed computing frameworks

- Familiarity with cloud platforms (AWS, Azure, or Google Cloud)

- Experience working in enterprise data environments

- Knowledge of data governance, compliance, and privacy regulations

Professional Skills

The successful candidate will demonstrate:

- Strong analytical and problem-solving capabilities

- Ability to think critically and interpret complex datasets

- Excellent written and verbal communication skills

- Ability to explain complex technical concepts to non-technical audiences

- Strong attention to detail and commitment to data quality

- Ability to manage multiple projects and priorities in a fast-paced environment

- Collaborative mindset with strong teamwork abilities

Compensation & Additional Information

Pay Rate: $48.00 per hour

BLOC Resources offers competitive compensation and the opportunity to work on meaningful data-driven initiatives with industry-leading organizations.

Additional benefits of working through BLOC Resources may include:

- Access to contractor support resources through BLOC Resources, including onboarding assistance and ongoing recruiter support.

- Opportunity to gain valuable experience working on high-impact data analytics and machine learning projects.

- Exposure to enterprise-level data environments and advanced technologies.

- Potential for contract extension or long-term placement based on performance and business needs.

- Professional support from the BLOC Resources recruiting and operations team throughout the duration of the assignment.

BLOC Resources is committed to connecting talented professionals with organizations where they can contribute, grow their careers, and make a meaningful impact through innovative data solutions.

1. Do you require work visa sponsorship now or in the future?

2. Have you built or implemented anything in Databricks (e.g., notebooks, jobs, dashboards,

ML workflows)?

3. How many years of hands-on experience do you have using SQL to pull, clean, and

transform data for analysis (e.g., building datasets/views, joins, window functions)?

4. Which programming languages do you primarily use (e.g. Python, SAS, R, SPSS)?

5. What types of models have you built most often (e.g., regression, classification, time series,

clustering)