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Senior Level Data Scientist

As a Senior Level Data Scientist with Maverc, you will take a leading role in designing, implementing, and optimizing advanced machine learning models and AI solutions that drive organizational success. You will lead technical initiatives, collaborate closely with cross-functional teams, and ensure the successful delivery of robust, scalable, and efficient data-driven solutions. In this role, you'll manage the integration of complex AI technologies such as NLP, generative AI, and large-scale data processing, all while ensuring alignment with the company’s strategic goals. You will be a key player in pushing the boundaries of innovation and ensuring the continuous improvement of our AI-driven products.

  • Design & Development: Lead the design, configuration, development, testing, and support of informatics and data science solutions for various technical use cases
  • Collaboration: Work closely with cross-functional teams, including data scientists and software engineers, to integrate AI solutions into Search Portfolio products, leveraging resources from the CDAO or DoD community
  • AI Model Optimization: Optimize AI models for performance, scalability, and efficiency using cloud-based resources and distributed computing frameworks, especially Apache Spark and Databricks
  • Research & Innovation: Stay updated on AI advancements and contribute to applying new research findings to enhance Search Portfolio products
  • Lifecycle Management: Manage the lifecycle of AI/ML components, from research and development to deployment and optimization
  • Data Analysis & Diagnostics: Apply analytical methodologies to diagnose and address data-related challenges, ensuring performance optimization
  • Documentation & Presentation: Document and present design alternatives, technical findings, and requirements to stakeholders
  • Data Modeling & Analysis: Develop strategic, baselined data modeling processes and accurately determine cause-and-effect relationships
  • Tool Development: Maintain and guide the development of common libraries and tools used across teams
  • Rapid Prototyping: Contribute to the formulation of strategies to achieve rapid prototyping
  • Extensive experience in machine learning (ML), including fields like Natural Language Processing (NLP), computer vision, and statistical learning theory
  • Hands-on expertise with NLP, Large Language Models, text embedding, semantic queries, generative AI for text, and retrieval-augmented generation (RAG)
  • Strong familiarity with data preprocessing, feature engineering, and model evaluation techniques essential for machine learning projects
  • Solid understanding of various ML algorithms (supervised and unsupervised learning, reinforcement learning, neural networks)
  • Proficient in version control systems such as Git for collaboration and code management
  • Experience in ML engineering or data science, specifically building ML models
  • Strong coding skills in Python, R, Scala, Java, or C++, with a focus on creating reproducible, well-documented code
  • Experience with Apache Spark and Databricks for distributed AI/ML workloads
  • Expertise in working with large datasets (petabytes), uncovering hidden patterns, using data visualization tools, and writing SQL queries
  • Experience with GPUs for model development
  • Proficient in cloud-based data persistence, particularly RDS PostgreSQL and PostgreSQL extensions like pgvector
  • Experience with persisting vectorized data from text embedding processes using Elastic and/or OpenSearch, and vector-enabled RDBMS like pgvector-enhanced PostgreSQL
  • Ability to communicate technical concepts effectively to business, technical, and lay audiences, with experience delivering data-driven presentations
  • Security Clearance: Minimum active Top Secret (TS) clearance with Sensitive Compartmented Information (SCI) eligibility

Education:

  • Bachelor’s Degree plus 7-10 years of experience, or
  • Master’s Degree plus 5 years of experience

**Join Maverc. Be Valued.**

At Maverc, we are an inclusive community where diversity in all its forms is embraced, respected, and recognized as a true asset to the company. We are dedicated to fostering this inclusive environment, though we acknowledge that there is always room for improvement. Maverc is committed to evolving into a more inclusive and equitable organization, upholding the principles of equal employment opportunity and affirmative action.

Maverc is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment based on gender, gender identity or expression, sexual orientation, race, age, religion, physical or mental disability, veteran status, or other protected characteristics under federal, state, and local laws.

As a federal contractor, Maverc has implemented affirmative action programs to ensure non-discrimination and promote affirmative action in our policies and practices for qualified women, minorities, protected veterans, and individuals with disabilities. The narrative portion of Maverc's affirmative action plans is available for inspection at our offices during normal business hours. Employees and applicants interested in reviewing these plans should contact Human Resources at or hr@maverc.com for assistance.

If you are interested in applying for a position with Maverc and require special assistance or accommodation to apply for a posted position, please contact our Human Resources department at hr@maverc.com or by calling 888-948-1468.

Exceptional People, Outstanding Benefits

Exceptional people are the cornerstone of any successful company. To attract and retain such talent, Maverc provides fulfilling work opportunities that complement a balanced lifestyle. We achieve this by offering exceptional benefits, enabling our employees to live and work well.

  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off (Vacation, Sick & Public Holidays)
  • Training & Development

Average salary estimate

$140000 / YEARLY (est.)
min
max
$120000K
$160000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Level Data Scientist, Maverc Technologies

As a Senior Level Data Scientist with Maverc, you'll find yourself at the forefront of innovation, leading the charge in designing and implementing high-performance machine learning models and AI solutions. In this pivotal role, your expertise will drive not just the technology, but the very success of our organization. You'll collaborate with diverse teams, bridging the gap between technical and strategic goals, and ensuring that our solutions are not just effective but also scalable. Your day-to-day will involve optimizing advanced AI technologies such as Natural Language Processing and large data processing frameworks. Additionally, you'll play a key role in researching new methods and tools that keep us ahead of the curve in the fast-paced tech world. With a strong emphasis on model lifecycle management and data analysis, your contributions will guide us in navigating complex, data-related challenges. Maverc values not just skills but the unique perspective each team member brings, and we are excited about your potential to help innovate our data-driven products. Join us in our commitment to creating an inclusive community where every voice matters and where your work truly reflects our collaborative spirit.

Frequently Asked Questions (FAQs) for Senior Level Data Scientist Role at Maverc Technologies
What are the key responsibilities of a Senior Level Data Scientist at Maverc?

As a Senior Level Data Scientist at Maverc, you'll engage in multiple responsibilities, including designing and developing machine learning models and AI solutions, leading cross-functional collaborations, and optimizing models for performance and scalability. This role demands continuous improvement in our AI technologies, requiring you to stay informed on the latest advancements in AI and contribute to innovative solutions.

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What qualifications are needed for the Senior Level Data Scientist position at Maverc?

To qualify for the Senior Level Data Scientist role at Maverc, you should possess a Bachelor’s Degree with 7-10 years of experience, or a Master’s Degree with 5 years. A deep understanding of machine learning, extensive coding skills in Python or R, experience with NLP, and knowledge of cloud-based technologies and distributed systems are crucial for success in this position.

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What tools and technologies does a Senior Level Data Scientist at Maverc work with?

At Maverc, Senior Level Data Scientists have hands-on experience with various tools and technologies such as Apache Spark, Databricks, RDS PostgreSQL, and advanced AI frameworks. You'll leverage cloud-based resources for model optimization and work with large datasets, employing tools for data visualization and SQL programming.

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How important is collaboration for the Senior Level Data Scientist role at Maverc?

Collaboration is critical for the Senior Level Data Scientist position at Maverc. You will work closely with cross-functional teams, including data scientists and software engineers, to integrate AI solutions into products, ensuring alignment with the company’s strategic goals. Your ability to communicate technical concepts to various stakeholders is essential for success.

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Does Maverc support training and development for Senior Level Data Scientists?

Absolutely! Maverc places a significant emphasis on training and development for its team members, including Senior Level Data Scientists. We offer exceptional benefits and opportunities that support both professional growth and personal well-being. Your continuous learning will help you stay at the forefront of technological advancements.

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Common Interview Questions for Senior Level Data Scientist
Can you explain how you approach building machine learning models?

When building machine learning models, I start with a clear understanding of the problem I’m solving. This involves careful selection of features, thorough data preprocessing, and defining success metrics. Each step is documented to ensure replicability, and collaboration with peers is encouraged to gain diverse insights.

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How do you optimize AI models for performance?

Optimizing AI models involves several strategies, including fine-tuning hyperparameters, utilizing cloud-based resources like Apache Spark for scalability, and implementing efficient data processing pipelines. Performance is continuously monitored, and adjustments are made based on real-time metrics.

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What methodologies do you use for data analysis and diagnostics?

I employ various analytical methodologies such as statistical analysis, exploratory data analysis (EDA), and machine learning algorithms. Utilizing tools like SQL for querying and data visualization platforms helps me understand patterns and issues in data effectively.

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Can you describe your experience with Natural Language Processing?

In my previous roles, I have implemented NLP techniques for various applications, including text classification, sentiment analysis, and language modeling. I leverage tools and libraries like NLTK and spaCy to preprocess and analyze large text datasets, aiming to extract meaningful insights.

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How do you handle the lifecycle management of AI/ML components?

Handling the lifecycle management of AI/ML components involves establishing structured protocols from initial research to deployment and optimization. I emphasize documentation, version control, and regular updates based on real-world performance feedback to ensure the models remain relevant.

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What coding languages are you proficient in, and how do they benefit your work?

I am proficient in Python, R, and Java, primarily using Python for building ML models due to its rich libraries. Having expertise in multiple languages allows me to choose the best tool for any given task, ultimately improving the efficiency and robustness of the solutions I develop.

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How do you stay updated on the latest trends in AI and data science?

I stay updated by regularly following industry blogs, attending conferences, participating in webinars, and engaging with the wider community through online forums like GitHub and Kaggle. Continuous learning is essential in the rapidly evolving field of AI.

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Can you provide an example of a challenging data-related issue you've resolved?

Certainly! In a past project, I faced a significant challenge with missing data sets affecting model performance. I implemented imputation techniques and data augmentation strategies, which improved the overall accuracy and reliability of the predictions.

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How do you effectively communicate technical concepts to non-technical stakeholders?

To communicate technical concepts effectively, I focus on simplifying jargon into relatable terms and utilize visuals to support my points. I tailor my presentations to address stakeholders' interests and concerns, emphasizing the practical implications of our data work.

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What role does team collaboration play in successful AI project execution?

Team collaboration is pivotal for successful AI project execution as it encourages the exchange of ideas and collective problem-solving. I prioritize establishing open channels for communication, ensuring alignment of goals and fostering a culture where everyone is encouraged to contribute.

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DATE POSTED
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