Explore the latest Data Science & Analytics job opportunities in 2025. Find entry-level, mid-level, and senior data engineer, machine learning engineer, and data analyst roles at leading companies including BlackRock, West Monroe, CVS Health, Ahold Delhaize, Target, and Disney. Apply directly today!
Data Science & Analytics Job Opportunities – Entry, Mid, and Senior Roles
The world of data science and analytics is growing at an unprecedented rate. Organizations across industries such as finance, healthcare, retail, entertainment, and technology are depending heavily on data professionals to make smarter decisions, optimize business processes, and improve customer experiences. Whether you are a new graduate, entry-level analyst, mid-level data engineer, or senior machine learning expert, 2025 is shaping up to be one of the strongest years for career opportunities in this space.
This guide brings you a curated list of the latest open roles in data engineering, machine learning, and analytics from some of the biggest names in the industry: BlackRock, West Monroe, CVS Health, Ahold Delhaize, Target, and Disney. Beyond job listings, we’ll dive into:
- The skills required for data roles in 2025.
- Career growth paths from entry to senior levels.
- Salary trends and high-demand domains.
- How to apply and stand out in competitive hiring markets.
Why Choose a Career in Data Science & Analytics?
- Explosive demand: LinkedIn and Glassdoor consistently rank data science and data engineering as some of the fastest-growing career paths.
- High salaries: According to PayScale and Glassdoor, average salaries range from $70,000 for entry-level analysts to $160,000+ for senior engineers and scientists in the U.S.
- Industry versatility: Data roles exist in nearly every sector – finance, healthcare, retail, logistics, and entertainment.
- Future-proof skills: AI, ML, cloud computing, and analytics will remain in demand, making this one of the most secure career paths.
📌 Featured Data Science & Analytics Job Listings
1️⃣ Data Engineer – BlackRock (📍 Princeton, NJ)
- Level: Mid-Level (~3+ years experience)
- Apply: BlackRock Careers
About the Role:
As a Data Engineer at BlackRock, you will help design and maintain scalable data pipelines supporting financial analytics, risk management, and portfolio optimization. BlackRock, a leader in asset management, deals with massive financial datasets requiring real-time processing and high reliability.
Key Responsibilities:
- Build and maintain ETL pipelines for large-scale financial data.
- Develop cloud-based solutions on AWS and Azure.
- Collaborate with data scientists and analysts to deliver real-time insights.
- Ensure compliance and governance for sensitive financial datasets.
Required Skills:
- Strong SQL and Python skills.
- Experience with Hadoop/Spark and cloud platforms.
- Data modeling and pipeline performance optimization.
2️⃣ Data Engineer – West Monroe (📍 Los Angeles, CA)
- Level: Mid-Level (1–4 years experience)
- Apply: West Monroe Careers
About the Role:
West Monroe, a management consulting firm, blends business strategy with technology innovation. As a Data Engineer here, you’ll work on consulting projects for Fortune 500 clients, focusing on data modernization and analytics transformation.
Key Responsibilities:
- Build and deploy data pipelines for enterprise clients.
- Design modern data architectures using Snowflake, Redshift, or BigQuery.
- Collaborate with consultants and business leaders to align data strategy.
Required Skills:
- SQL, Python, and cloud-native data tools.
- Familiarity with BI tools like Tableau or Power BI.
- Strong communication and client-facing skills.
3️⃣ Machine Learning Engineer – CVS Health (📍 Chicago, IL)
- Level: Entry-Level (~1 year experience)
- Apply: CVS Health Careers
About the Role:
CVS Health is leveraging AI and machine learning to improve patient outcomes, enhance operational efficiency, and drive innovation in healthcare. As a Machine Learning Engineer, you’ll work with healthcare data pipelines and predictive models.
Key Responsibilities:
- Develop ML models for healthcare prediction and patient care.
- Work on NLP applications for unstructured medical data.
- Deploy ML pipelines in cloud environments.
Required Skills:
- Knowledge of Python, TensorFlow/PyTorch, and scikit-learn.
- Experience with cloud platforms (AWS/GCP/Azure).
- Familiarity with healthcare data standards (HIPAA compliance).
4️⃣ Data Engineer – Ahold Delhaize (📍 Quincy, MA)
- Level: Entry-Level (~2 years experience)
- Apply: Ahold Delhaize Careers
About the Role:
Ahold Delhaize, a global retail group, is focused on using data to improve customer personalization and optimize supply chain efficiency. As a Data Engineer, you’ll work on retail analytics and customer insights.
Key Responsibilities:
- Develop ETL processes for retail data.
- Collaborate with analysts to improve customer personalization.
- Manage structured and unstructured datasets at scale.
Required Skills:
- SQL and Python proficiency.
- Familiarity with retail data systems.
- Cloud data engineering experience.
5️⃣ Data Analyst – Target (📍 Brooklyn Park, MN)
- Level: Entry-Level (0–2 years experience)
- Apply: Target Careers
About the Role:
Target, one of the largest retailers in the U.S., depends on analytics for everything from inventory optimization to customer loyalty programs. Data Analysts play a crucial role in analyzing performance metrics and reporting insights.
Key Responsibilities:
- Collect and clean retail and e-commerce data.
- Use BI tools (Tableau, Power BI) for visualization and reporting.
- Present actionable insights to business leaders.
Required Skills:
- SQL, Excel, and visualization skills.
- Analytical problem-solving mindset.
- Strong communication skills.
6️⃣ Analyst – Analytics & BI – Disney Experiences (📍 Celebration, FL)
- Level: Entry-Level (~2 years experience)
- Apply: Disney Careers
About the Role:
Disney Experiences uses analytics to enhance customer engagement, personalize experiences, and optimize theme park operations. This is a great opportunity for entry-level professionals passionate about business intelligence and customer analytics.
Key Responsibilities:
- Work with large datasets from entertainment and hospitality operations.
- Build BI dashboards and reports for leadership teams.
- Apply predictive analytics to enhance customer engagement.
Required Skills:
- SQL, Excel, Tableau, or Power BI.
- Ability to analyze customer journey data.
- Strong storytelling and data visualization.
📊 In-Demand Skills for Data Science & Analytics Jobs
- Programming Languages: Python, R, SQL, PySpark.
- Cloud Platforms: AWS, Azure, Google Cloud.
- Big Data Tools: Hadoop, Spark, Kafka.
- ML & AI Frameworks: TensorFlow, PyTorch, scikit-learn.
- Data Visualization: Tableau, Power BI, Looker.
- Data Engineering Tools: Snowflake, Redshift, Databricks.
- Soft Skills: Problem-solving, storytelling with data, collaboration.
💰 Salary Trends in Data Roles
- Data Analysts: $65,000 – $85,000 (entry-level U.S. average).
- Data Engineers: $90,000 – $130,000 (mid-level U.S. average).
- Machine Learning Engineers: $100,000 – $150,000.
- Senior Data Scientists/Leads: $140,000 – $180,000+.
In India, salaries range between ₹6 LPA (entry-level analysts) to ₹35–45 LPA (senior machine learning engineers).
🚀 Career Pathways in Data Science & Analytics
- Entry-Level Roles: Data Analyst, Junior Data Engineer, ML Associate.
- Mid-Level Roles: Data Engineer, BI Analyst, ML Engineer.
- Senior-Level Roles: Data Architect, Lead Data Scientist, Head of Analytics.
📝 How to Apply & Stand Out
- Tailor your resume to highlight skills like SQL, Python, and cloud experience.
- Showcase projects on GitHub or Kaggle.
- Earn certifications in AWS Data Engineering, Google Cloud ML, or Azure AI.
- Network actively on LinkedIn and through data science communities.
❓ FAQs
Q1: Do I need a master’s degree to land a data science role?
Not always. Many entry-level jobs accept strong project portfolios and certifications instead of advanced degrees.
Q2: Which is better – Data Engineer or Data Scientist?
Both are valuable. Engineers focus on building pipelines, while scientists focus on modeling. Demand is strong for both.
Q3: Can fresh graduates apply for these roles?
Yes, companies like CVS, Disney, and Target are actively hiring new grads and entry-level candidates.
Q4: What’s the most in-demand tool in 2025?
Python remains the top programming language, but cloud and AI tools (Databricks, TensorFlow, Azure ML) are surging.
The data science and analytics job market in 2025 offers unprecedented opportunities across industries. Whether you’re just starting as a data analyst or looking to step into senior-level ML engineering roles, companies like BlackRock, CVS Health, Target, and Disney are opening doors to promising career paths.
Take the time to apply directly via official career portals, prepare well, and showcase your technical expertise. The future of data belongs to those ready to harness it.
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