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Senior Data Science Lead - R01544683

About Brillio:


Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.

Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.


Senior Data Science Lead


Primary Skills
  • Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio


Specialization
  • Data Science Advanced: Data Science Lead


Job requirements
  • Title: ML Architect
  • Location: Chicago, IL
  • Onsite model

  • The ML Architect designs and deploys scalable machine learning systems, ensuring models are production-ready, secure, and efficient. This role focuses on building ML pipelines, deploying models, and maintaining best practices for MLOps.

Qualifications:
  • Bachelor's or Master’s Degree in Computer Science, Data Engineering, Machine Learning, or related field.
  • Preferred: Certification in cloud platforms (Azure, AWS, GCP) or MLOps.
  • Experience:
  • 7-9+ years of experience in machine learning, software engineering, or data engineering.
  • 3-4 years of experience deploying ML models in production environments.
  • Experience with cloud platforms, MLOps practices, and large-scale systems in the QSR or retail industry is highly beneficial.

Key Skills:
  • System Design & Architecture:
  • o   Experience designing and deploying machine learning systems that scale across thousands of locations.
  • o   Building real-time recommendation engines for digital ordering platforms.
  • Model Deployment & MLOps:
  • o   Proficiency in MLOps practices for continuous integration, delivery, and deployment (CI/CD).
  • o   Familiarity with cloud-based ML services (Azure ML, SageMaker, GCP Vertex AI).
  • o   Experience in containerization (Docker) and orchestration (Kubernetes).
  • o   Knowledge of serverless computing and cloud-native services.
  • Inventory & Supply Chain Optimization:
  • o   Building ML solutions for supply chain forecasting, inventory optimization, and waste reduction.
  • Fraud Detection & Risk Management:
  • o   Experience in implementing fraud detection systems for payment processing and loyalty programs.
  •  
  • Recommendation Systems:
  • o   Developing personalized upsell and cross-sell recommendations for digital ordering systems.
  • Performance Optimization:
  • o   Ability to optimize model performance and latency for real-time applications.
  • o   Experience with distributed computing frameworks (Spark, Dask).
  • Security & Compliance:
  • o   Ensuring deployed models comply with data privacy regulations (e.g., GDPR, CCPA) and security best practices.
  • Collaboration & Documentation:
  • Ability to collaborate with data scientists, engineers, and DevOps teams.
  • Strong documentation skills for model architecture and deployment processes.


Why should you apply for this role?
As Brillio continues to gain momentum as a trusted partner for our clients in their digital transformation journey, we strive to set new benchmarks for speed and value creation. The DI team at Brillio is at the forefront of leading this charge by reimagining and executing how we structure, sell and deliver our services to better serve our clients.

 
Know what it’s like to work and grow at Brillio: https://www.brillio.com/join-us/
 
Equal Employment Opportunity Declaration
Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.
 
#LI-SR1


$160,000 - $170,000 a year

 

Know what it’s like to work and grow at Brillio: Click here

Average salary estimate

$165000 / YEARLY (est.)
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$160000K
$170000K

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What You Should Know About Senior Data Science Lead - R01544683, Brillio

Are you ready to take your career to the next level? Join Brillio as a Senior Data Science Lead in beautiful Chicago, Illinois! At Brillio, we are a rapidly growing digital technology service provider, and we pride ourselves on being at the forefront of innovation for many Fortune 1000 companies. We're looking for a talented individual who is passionate about data science and machine learning. In this role, you'll leverage your expertise in hypothesis testing, regression analysis, and various ML frameworks to lead projects that make a difference. You'll be involved in designing and deploying scalable machine learning systems that are both efficient and secure. Your work will directly contribute to our reputation as an employer of choice while helping our clients navigate their digital transformation journey successfully. If you have extensive experience in deploying models in production and a strong background in Python, ML architectures, and MLOps, we want to hear from you! Your contributions will play a crucial role in optimizing processes and building innovative ML solutions such as recommendation systems and fraud detection. With a competitive salary range of $160,000 - $170,000 a year, this is an exciting opportunity to join a collaborative team that values your skills and promotes your growth. Come be a part of Brillio, where our commitment to our Brillians ensures a thriving environment for personal and professional development.

Frequently Asked Questions (FAQs) for Senior Data Science Lead - R01544683 Role at Brillio
What are the key responsibilities of a Senior Data Science Lead at Brillio?

As a Senior Data Science Lead at Brillio, you will primarily focus on designing and deploying scalable machine learning systems, ensuring models are production-ready, and managing the ML pipeline. You'll work closely with cross-functional teams to optimize model performance, implement MLOps best practices, and develop innovative ML solutions tailored for our clients.

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What qualifications do I need to apply for the Senior Data Science Lead role at Brillio?

To qualify for the Senior Data Science Lead position at Brillio, candidates should possess a Bachelor's or Master's Degree in Computer Science, Data Engineering, or related fields. Additionally, having 7-9 years of experience in machine learning or data engineering, along with proficiency in deploying ML models in production environments, is essential.

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What technical skills are necessary for the Senior Data Science Lead position at Brillio?

Candidates for the Senior Data Science Lead role at Brillio should have expertise in Python, various ML frameworks like TensorFlow and PyTorch, and experience with MLOps practices, cloud platforms, and systems design. Knowledge of System Design & Architecture, inventory optimization, and fraud detection solutions is also crucial.

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What is the work environment like for a Senior Data Science Lead at Brillio?

At Brillio, our work environment is collaborative and dynamic. As a Senior Data Science Lead, you'll work with a talented group of professionals who prioritize innovation and client satisfaction. We believe in a strong culture of support and professional growth, ensuring that our Brillians thrive in their roles.

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Why should I consider working for Brillio as a Senior Data Science Lead?

Brillio offers an excellent opportunity for growth and development in the field of data science. With a focus on cutting-edge technologies and a commitment to digital transformation, you will play a key role in shaping the future for our clients. Coupled with a supportive culture and competitive compensation, Brillio is the place to advance your career.

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Common Interview Questions for Senior Data Science Lead - R01544683
Can you explain your experience with deploying machine learning models in production?

When answering this question, emphasize specific projects where you successfully deployed ML models. Detail the challenges faced, the tools used (like Docker or Kubernetes), and how you ensured model performance and compliance with best practices.

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How do you approach designing scalable machine learning systems?

Discuss your systematic approach to system design, including understanding requirements, selecting appropriate architectures, and ensuring scalability through cloud services or distributed computing. Provide examples from your previous work whenever possible.

Join Rise to see the full answer
What is your experience with MLOps practices?

Highlight your familiarity with MLOps frameworks for continuous integration and delivery. Discuss tools you've used and how you've implemented these practices in past projects to streamline model deployment and monitoring.

Join Rise to see the full answer
Describe a time you optimized a model for performance.

When describing your experience, focus on the methods you used for optimization, such as algorithm adjustments, feature engineering, or refining hyperparameters. Explain the impact it had on the model’s performance metrics.

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How do you ensure data privacy and compliance in your models?

Mention the strategies you've employed to adhere to data privacy regulations, such as GDPR or CCPA. Detail your experience with data anonymization, securing data access, and monitoring compliance during model deployment.

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What machine learning frameworks are you most experienced with?

Provide insights into the frameworks you have used, such as TensorFlow, PyTorch, or Scikit-learn, and discuss the types of projects or applications you implemented using these tools, emphasizing your hands-on experience.

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How do you measure the success of a machine learning model?

Discuss your approach to evaluating model performance using metrics such as accuracy, precision, recall, and F1 score. Provide examples of specific projects where you utilized these metrics to assess and improve your models.

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What strategies do you use for effective collaboration with cross-functional teams?

Highlight your communication skills and approach to collaboration. Discuss how you facilitate discussions among team members from data engineering, DevOps, and business units to ensure alignment on machine learning projects.

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Can you discuss your experience in building recommendation systems?

Share specific examples of recommendation systems you have developed in the past, detailing the algorithms used and how you tailored them for user behavior or preferences to enhance personalization.

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What challenges have you faced in machine learning projects, and how did you overcome them?

Reflect on a specific challenge, such as data quality issues or model deployment hurdles, and discuss the proactive strategies you employed to resolve the issue, demonstrating your problem-solving skills.

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Full-time, on-site
DATE POSTED
January 5, 2025

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