Senior Data Architect And Data Scientist Jobs

Ensure the quality and proper management of data assets across the data lifecycle.

Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.

World Class Mentorship and Training: Working with renowned, published leaders and academics in machine learning to further develop your skillsets.

Develop and maintain data / ML engineering solutions based on requirements and design specifications using appropriate tools and technologies.

Create design and development documentation based on standards for knowledge transfer, training, and maintenance.

Work with business and products teams to understand requirements, and translate them into technical needs. 

Leading Edge Tech Stack: Experience build products that will be deployed globally on a leading-edge tech stack.

World Class Mentorship and Training: Working with renowned, published leaders and academics in machine learning to further develop your skillsets.

Previous experience (through co-op or internship) as a data scientist preferred.

Apply data science expertise in machine learning, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects.  

Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies. 

Work on full-spectrum of activities, from conducting ML experiments to delivering production-ready models. 

Collaborate with management, staff and stakeholders on data strategy, architecture, rationalization, quality, and analytics to support strategic business initiatives

Develop Logical and Physical Data Models to ensure adherence to sound data management principles

5 plus years of Azure SQL management

Provide end-to-end vision and knowledge to projects to help better design solutions

7 plus years of Database Administration experience on MSSQL

5 years of general data analysis experience including excellent understanding of SQL and complex queries

Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes

Translate complex concepts into implications for the business via excellent communication skills, both verbal and written

3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting

Significant experience with SQL and large unstructured datasets such as Hadoop

Strong verbal and written communication skills

Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

BS or higher in a quantitative discipline (Statistics, mathematics, qualitative social science, operation management, finance, physics) or equivalent working experience

Work with Legal and Compliance on model review and approval, satisfy governance requirement

Years of hands-on experience with data science and statistical modeling

Solid analytical skills and an understanding of how to utilize data to target improvements, solve problems, and provide data-driven insights

Strong organization skills and the ability to communicate effectively, both verbally and in written

Exceptional problem-solving skills and ability to work effectively with minimal Comfortable working both independently and in a team environment.

Strong programming skills in Python and experience with Machine Learning tools (numpy, scipy,scikit-learn, pandas, pytorch/ tensorflow, ...)

Strong knowledge of data science algorithms and their limitations (execution speed, memory considerations, etc)

Experience dealing with very large datasets

Familiarity with database environments (including distributed big data solutions) and functional SQL knowledge

Experience with cloud providers (AWS, GCP, Azure)

Research: Discover solutions to unique data science challenges while satisfying business needs

Develop strong partnerships with key stakeholders within Business, IT, Program/Product, Marketing, and Finance to identify business requirements and expected outcomes

Provide ongoing thought leadership to testing programs, R&D management, or other management concerns

Education, Certifications, or Special Licenses

Improve the enterprise’s knowledge of emerging technologies, frameworks, and trends in AI (Artificial Intelligence) and ML

Work with IT teams to support data collection, integration and retention requirements based on input collected with the business

Assess, with the business, the expected qualification and assurance of the information in support of the use case(s)

Working knowledge of statistical applications/software (Redshift SQL, "Oracle" SQL, python, R, etc) and experience with Excel and Powerpoint

Minimum 3 years of work experience in a non-academic setting

Minimum 5 years of experience in an analytical business function

Working knowledge of Pharmaceutical industry data sources/business models would be an asset

Master’s degree in Statistics, Mathematics, Physics, Computer Science, Engineering, or related fields with an emphasis on statistics and business analysis.

Proficiency in advanced mathematics/statistics (regressions, optimization, clustering analysis, predictive modeling etc.) and data mining

Three years of relevant experience in credit risk or portfolio management

Exceptional organization skills to prioritize, manage, and implement a variety of competing initiatives, on a concurrent or staggered basis

Manage collections analytics, performance monitoring and strategy evaluation routines

Strong collaboration and communication skills

Experience with statistical software packages such as R or SAS

Experience manipulating large and complex databases

Ability to influence prioritization and execution of high impact projects effecting customer experience, monetization, and marketing’s roadmap

You will have the seat at the table for every key decision for growth and marketing strategies

You will create a culture of strong technical ownership, resulting in highly reliable products and services at scale

You will leverage data-driven insights to proactively identify most impactful opportunities, and inform future experimentation design and product roadmaps

Masters’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field

Build and manage a high-performing data team

Develop quick proofs of concept to showcase capabilities and potential

At least 3 years experience in spearheading custom machine learning solutions

Client servicing experience is a must

Experience in the Financial Services and Retail industries

Experience in sales, service and marketing use cases

Experience in enterprise level ML product development is required.

Execute data science innovation topics for Forecast Engine Utility and Integrated Business operations to deliver global forecast KPIs

Analyzing the AI/ML algorithms that could be used to solve a given problem and ranking them by their success probability.

Actively contribute to and re-use UL DS community best practices.

Working in an agile environment with globally distributed teams.

Mentor and supervise team member across the organization.

• Work closely with Machine Learning, Engineering and Product teams to understand requirements and help build solutions.

• 5+ years of professional experience in data science focusing on AI/ML products.

• Experience working with natural language data (experience working with large language models is a plus)

• Experience in one or more programming languages (e.g., Python, Scala, etc.).

• Experience in one or more Statistical or mathematical software (E.g.,SAS, or Matlab, etc.).

• Experience in database modeling, SQL, and data warehousing principles.

A strong problem solver with critical thinking skills who can formulate a problem into a solution.

Experienced in architecting end-to-end solutions for production deployment (considered an asset but not required).

Analyzing complex, high-volume data from varying sources and identifying key regularities, patterns and trends.

Prototyping and developing machine learning models in collaboration with an agile, high-functioning team.

Implementing effective monitoring and benchmarking for model performance comparison.

Leveraging new research in data modeling to identify opportunities, pioneering algorithms and systems that become key commercial products.

Experience leading projects and mentoringteam members

Experience with one or more deep learning technologies and frameworks (NLP, image analysis, generative models)

A comprehensive benefits package including medical, dental, vision, and generous mental health support options– all available on day 1

Statistical modelling: You’ll develop and implement advanced statistical models and algorithms to solve complex business problems

Product Insights and Strategy: Collaborate with cross-functional teams to translate data insights into actionable recommendations for product roadmap planning and strategy

High level of proficiency in statistical modeling and machine learning (e.g. feature engineering and selection, regression, classification, NLP, etc.)

Lead discovery sessions with primary business stakeholders to obtain knowledge of business objectives, challenges, and requirements

Support the identification of opportunities for continuous improvement of solution management methodologies, including obtaining feedback after the solution has been implemented

Strong knowledge of SQL and demonstrated ability to apply SQL to a wide variety of business requirements.

Support solution delivery by providing insights to the application development teams and project managers that plan and execute delivery activities

Create solution architecture documents that describe and explain solution attributes and associated benefits

Bachelor's degree in Information Technology, Software Engineering, Computer Science, or related field. Related professional certifications and/or training is considered an asset.

Designing, implementing and maintaining these analysis pipelines (typically in Python), ensuring data integrity, correctness, clarity and adherence to regulatory requirements.

You have experience with high throughput and/or IND-enabling scientific workflows.

You’re driven to learn and master new technical skills.

PhD, MSc or BSc in computer science, statistics, the sciences or a related field with 6+ years of related work experience.

Experience collecting or analyzing laboratory datasets.

Collaborating with scientists to develop standard protocols to execute and capture results from medium and high throughput experiments.

Experience and Skill Set Requirements

·Experience reporting progress on deliverables to team, project leads and management, including proactively raising risks/issues with mitigations

·Demonstrated skills in Python, RStudio, financial, business intelligence and data visualization development experience

·Experience gathering user requirements to develop a solution for data scientists

·Basic knowledge and experience with Azure DevOPS

·Excellent meeting facilitation skills to gather requirements

    Experience dealing with large datasets;

    Experience with Python and SQL, with the ability to create complex queries and joins;

    Strong data analysis and data modeling skills;

    Experience with data analytics tools in AWS or other cloud computing environments;

    Experience with machine learning (supervised or unsupervised);

    Experience with data manipulation and designing and implementing ETL processes;

Collaborate, coach, and learn with a growing team of experienced Data Scientists.

Hands-on experience building models is a must.

Experience with supply chain/retail forecasting is a must.

Exceptional communication and collaboration skills to understand business partner needs and deliver solutions.

Effectively communicate the analytics approach and how it will meet and address objectives to business partners.

Advocate and educate on the value of data-driven decision-making; focus on the “how and why” of solutions.