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Urgently Hiring Data Science Engineer Jobs (NOW HIRING)

This is not a pure engineering role or a pure research role. You'll need both, and you'll need to move fluidly between them. What You'll Do: Data Science & Applied ML * Research, prototype, and ...

$78K - $106K/yr

This is not a pure engineering role or a pure research role. You'll need both, and you'll need to move fluidly between them. What You'll Do: Data Science & Applied ML * Research, prototype, and ...

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Urgently Hiring Data Science Engineer information

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$44.5K

$129.7K

$177.5K

How much do urgently hiring data science engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for urgently hiring data science engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What does a data science engineer do?

An Urgently Hiring Data Science Engineer is responsible for quickly joining a team to design, develop, and implement data-driven solutions using advanced analytics, machine learning, and statistical methods. They work with large datasets, build data pipelines, and create predictive models to solve business problems. This role often requires collaborating with other engineers, data analysts, and business stakeholders to deliver actionable insights and support decision-making processes. The 'urgently hiring' aspect means employers are looking to fill the position as soon as possible due to immediate project needs or company growth.

What are the key skills and qualifications needed to thrive as a data science engineer?

To thrive as a Data Science Engineer, you need a strong background in statistics, programming (Python or R), and data modeling, typically supported by a degree in computer science, mathematics, or a related field. Proficiency with machine learning frameworks (such as TensorFlow or Scikit-learn), big data tools (like Spark or Hadoop), and cloud platforms (AWS, GCP, or Azure) is often expected, along with relevant certifications. Exceptional problem-solving, communication, and collaboration skills help you translate complex data insights into business value and work effectively with multidisciplinary teams. These skills and qualities are crucial for building effective data-driven solutions and maximizing organizational impact.

What are some common challenges faced by data science engineers when collaborating with cross-functional teams?

Data Science Engineers often work closely with product managers, software engineers, and business analysts, which can present challenges such as aligning on project goals, managing different priorities, and ensuring clear communication of complex technical concepts. It is crucial to translate data-driven insights into actionable business strategies that non-technical stakeholders can understand. Effective collaboration requires both technical expertise and strong interpersonal skills to bridge the gap between data science and other departments, ensuring that projects stay on track and deliver meaningful results.

What is the difference between Urgently Hiring Data Science Engineer vs Data Analyst?

AspectUrgently Hiring Data Science EngineerData Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; experience with programming languages like Python or RBachelor's in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentTech companies, startups, or industries requiring advanced modeling and machine learningBusiness intelligence, marketing, finance, or operations teams analyzing data for insights
Employer & Industry UsageUsed in industries focusing on predictive modeling, AI, and complex data solutionsCommon in industries needing data reporting, dashboards, and descriptive analytics

The main difference is that a Data Science Engineer focuses on building predictive models and machine learning solutions, requiring advanced technical skills, while a Data Analyst primarily interprets data through reports and visualizations. The urgency in hiring indicates immediate project needs for the Data Science Engineer role.

Are data science engineers still in demand?

Data science engineers are currently in high demand due to the increasing reliance on data-driven decision making across industries. They are sought after for their skills in machine learning, statistical analysis, and programming languages like Python and R, often requiring knowledge of big data tools such as Hadoop or Spark. The role remains critical as organizations prioritize AI and analytics initiatives.
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Infographic showing various Urgently Hiring Data Science Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Machine Learning / Data Science Engineer

Richmond, VA • On-site

CapTech Consulting
IT Services • 501 - 1,000 employees

$113K - $136K/yr

Full-time

Medical, Retirement, PTO

Re-posted yesterday


Job description

Company Description

CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.

Job Description

CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.

Specific responsibilities for the Machine Learning Engineer position include:

  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
Qualifications
  • Bachelor's degree or equivalent combination of education and experience.
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting 
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures 
  • Strong understanding of conversational UX and prompt evaluation metrics 
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration
Additional Information

We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions.  You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way.  Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs. 

  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  • Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
  • Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities. 
  • 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness - each foundational to our core values.  We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE.  As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email [email protected].

CapTech supports Equal Pay for all. In addition, in the State of Virginia, we are committed to Equal Pay for ALL in accordance with the Virginia Transparency Law. Compensation for this role will be commensurate with the candidate's skills, total relevant experience, job level, and geographic location. The base pay range for this role is: $90,000 - $200,000.

At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship. Â