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Full Time Nba Data Science Jobs (NOW HIRING)

Data Scientist

Santa Monica, CA · On-site

$80 - $100.72/hr

This role focuses on building data science and AI-driven solutions, including predictive patient event modeling, Next Best Action (NBA) engines for HCP engagement, and GenAI-powered decision agents ...

Lead the migration of historical viewership data from its current data repository to the NBA ... Work with DSA's Data Science team on data modeling efforts for the purposes of advanced analytics ...

Director, Insights, NBA

Novato, CA · On-site

$176K - $261K/yr

Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers ... Regular, full-time employees are also eligible for a range of benefits at the Company, including ...

The NBA currently provides eligible employees the option of working remotely one day per week ... Collaborate with advanced insights and data science teams on predictive modeling, segmentation, and ...

Oversee development and deployment of pricing models across major sports and esports (NBA, NFL, CS2 ... In addition to your great compensation package, full-time employees will be eligible for the ...

One of our clients, a fast growing FinTech company that provides an online marketplace for commercial loans to small businesses, is looking to hire a full-time Director, Data Science to lead ...

You will join an existing Analytics and Data Science department, and partner with IDT's new AI Lab ... Improve and scale next-best-action (NBA) engines to enhance personalized user experiences.

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

... full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high ... Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science ...

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Full Time Nba Data Science information

How to become an NBA data analyst?

To become an NBA data analyst, you typically need a bachelor's degree in a related field such as statistics, data science, or sports management. Developing skills in programming languages like Python or R, proficiency with data visualization tools, and knowledge of basketball analytics are essential. Gaining experience through internships or projects related to sports data can also improve job prospects.

What is the difference between Full Time Nba Data Science vs Full Time Nba Data Analyst?

AspectFull Time Nba Data ScienceFull Time Nba Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills (Python, R); knowledge of machine learningDegree in Data Analysis, Statistics, or related; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative, technical teams; focus on modeling and predictive analyticsBusiness-focused; interpret data for decision-making, reporting, and insights
Employer & Industry UsageNBA teams, sports analytics firms, media companiesNBA teams, sports media, marketing agencies

Full Time Nba Data Science roles typically require advanced technical skills and focus on developing predictive models, while Full Time Nba Data Analysts concentrate on interpreting data for strategic decisions. Both roles are integral to NBA organizations but differ in technical depth and focus areas.

Is 30 too late for data science?

Full Time NBA Data Science roles typically require strong analytical skills, programming knowledge, and experience with sports data. Age is generally not a barrier if you have relevant skills, a solid portfolio, and demonstrate continuous learning through courses or certifications. Many professionals transition into data science later in their careers successfully.

How much does an NBA data scientist make?

An NBA data scientist typically earns between $70,000 and $130,000 annually, depending on experience, education, and the organization. Salaries can vary based on skills in data analysis, machine learning, and familiarity with sports analytics tools.

Do NBA teams have data scientists?

Yes, many NBA teams employ data scientists to analyze player performance, game strategies, and injury prevention. These professionals often use statistical tools, machine learning, and data visualization to support team decisions and improve performance.
More about Full Time Nba Data Science jobs
What cities are hiring for Full Time Nba Data Science jobs? Cities with the most Full Time Nba Data Science job openings:
What are the most commonly searched types of Nba Data Science jobs? The most popular types of Nba Data Science jobs are:
What states have the most Full Time Nba Data Science jobs? States with the most job openings for Full Time Nba Data Science jobs include:
Data Scientist

Data Scientist

Lancesoft

Santa Monica, CA • On-site

$80 - $100.72/hr

Full-time

Posted 13 days ago


Job description

Job Description
Job Title: Data Scientist III
Location: 100% Remote
Contract Duration: 12 Months
Pay Range: $80.00 - $100.72 USD hourly on W2

Job Description:
We are seeking a highly motivated Data Scientist to join the Global Data & Digital Innovation (GDDI) organization within the pharmaceutical commercial domain. This role focuses on building data science and AI-driven solutions, including predictive patient event modeling, Next Best Action (NBA) engines for HCP engagement, and GenAI-powered decision agents to enhance commercial effectiveness.
The ideal candidate will combine strong machine learning expertise with experience in GenAI agent development and scalable ML pipelines, enabling actionable insights for stakeholders across GDDI, Sales, Marketing, Sales Analytics, and Advanced Analytics functions.
Key Responsibilities
Develop and deploy predictive models for patient events (line switches, initiation)
Scale Next Best Action (NBA) solutions to optimize HCP engagement strategies across channels to various products
Apply advanced ML techniques including regression, classification, and NLP techniques
Create multi touch attribution pipelines for the customer journeys and optimization
Integrate GenAI capabilities into commercial workflows such as:
HCP engagement planning
Content personalization
Gen AI interfaces for ML pipelines
ML Engineering & Pipeline Development
Oversee build and maintenance of end-to-end ML pipelines including:
Data ingestion, feature engineering, model training, evaluation, and deployment
Implement MLOps best practices:
Model versioning, monitoring, and retraining pipelines
CI/CD integration for scalable deployment
Work with modern data platforms (e.G., Databricks, AWS)
Commercial Strategy & Stakeholder Support
Partner with Sales, Marketing, and Sales Analytics teams to translate business problems into analytical solutions
Deliver actionable insights and recommendations to senior stakeholders
Collaborate with:
Advanced Analytics teams (modeling and experimentation on alerts)
Data Engineering teams (data pipelines and infrastructure)
Business stakeholders (Sales, Marketing, Market Access)
Act as a bridge between technical and business teams, ensuring adoption of advanced analytics and AI solutions
Data Management & Compliance
Work with large-scale healthcare datasets such as:
Claims, EHR/EMR, CRM, and digital engagement data
Ensure compliance with data privacy and regulatory standards (e.G., HIPAA)
Required Qualifications
Education
Master s or PhD in:
Data Science
Computer Science
Statistics
Operations Research
Mathematics or a related quantitative discipline
Experience
5-7+ years (Master s) or 3 5+ years (PhD) in:
Data science, machine learning, or advanced analytics
Pharmaceutical / life sciences commercial analytics preferred
Healthcare analytics or consulting experience
Technical Skills
Core Data Science
Proficiency in:
Python (preferred) or R
SQL
Strong understanding of:
Machine learning algorithms (supervised/unsupervised learning)
Statistical analysis and experimental design
GenAI & Modern AI Stack
Hands-on experience with:
Large Language Models (LLMs) and GenAI frameworks
Prompt engineering and RAG architecture
Agent-based AI systems (e.G., LangChain, MCP, A2A, AutoGen)
Familiarity with:
Vector databases and embeddings
API-based AI integrations
ML Engineering / MLOps
Experience with:
Overseeing ML pipelines (training deployment monitoring)
Tools such as Databricks, Azure ML, AWS SageMaker
Knowledge of:
Model deployment, REST APIs, containerization (Docker)
CI/CD pipelines for ML systems
Visualization & Communication
Ability to build apps for demo purposes using Databricks
Experience with BI tools (Power BI, Tableau)
Strong storytelling skills to communicate insights effectively
Domain Expertise (Preferred)
Pharmaceutical commercial domain experience, including:
Patient journey and longitudinal data analysis
HCP targeting and segmentation
Omnichannel marketing analytics and campaign optimization
Experience in:
Next Best Action (NBA) frameworks
Sales force effectiveness
Promotional response modeling especially Multi- touch Attribution
Key Competencies
Strong problem-solving mindset with business acumen
Ability to bridge AI innovation with commercial impact
Excellent stakeholder management and communication skills
Experience working in cross-functional, global teams
High attention to detail and commitment to quality
What Success Looks Like
Delivering scalable AI/ML and GenAI solutions that drive commercial insights
Enabling smarter, real-time decision-making for Sales and Marketing teams
Successfully deploying GenAI agents and production-grade ML pipelines
Becoming a trusted partner within the Global Data & Digital Innovation organization
Meet Your Recruiter
Medhaj Gajjar

LanceSoft logo

About LanceSoft

Sourced by ZipRecruiter

Established in 2000, LanceSoft is a Certified MBE and Woman-Owned organization. Lancesoft Inc. is one of the highest rated companies in the industry. We have been recognized as one of the Largest Staffing firms and ranked in the top 50 fastest Growing Healthcare Staffing firms in 2022. Lancesoft offers short- and long-term contracts, permanent placements, and travel opportunities to credentialed and experienced professionals throughout the United States. We pride ourselves on having industry leading benefits. We understand the importance of partnering with an expert who values your needs, which is why we're 100% committed to finding you an assignment that best matches your career and lifestyle goals. Our team of experienced career specialists takes the time to understand your needs and match you with the right job Lancesoft has been chosen by Staffing Industry Analysts as one of the Best Staffing Firms to Work for.LanceSoft specializes in providing Registered Nurses, Nurse Practitioners, LPNs/LVNs, Social Workers, Medical Assistants, and Certified Nursing Assistants to work in Acute Care Centers, Skilled Nursing Facilities, Long-Term Care centers, Rehab Facilities, Behavioral Health Centers, Drug & Alcohol Facilities, Home Health & Community Health, Urgent Care Clinics, and many other provider-based facilities.

Industry

Recruiting and staffing services

Company size

1,001 - 5,000 Employees

Headquarters location

Herndon, VA, US

Year founded

2000

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