Data Scientist Student Jobs

Ability to write data management and analysis programs using data programming tools such as R or Python.

Skills in designing in simulation modelling in the context of evaluating public health measures.

Experience managing and querying data in large relational or multidimensional databases and data warehouses an asset.

Knowledge of standard software packages, spreadsheet, statistical, graphical, database, communication and web software.

PHSA is a remote work friendly employer, welcoming flexible work options to support our people (eligibility may vary, depending on position).

Proficiency in utilizing advanced statistical techniques for analyzing complex datasets, including longitudinal data analysis.

0-3+ years of professional experience for PhDs or 2-5+ years for Master’s in a data scientist role

End-to-end experience with data, including querying, aggregation, analysis, and visualization

Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Extended health and dental coverage options, along with life insurance and disability benefits

Perform exploratory data analysis to gain a deeper understanding of problems

Develop and fit statistical, machine learning, or optimization models

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. 

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. 

10+ years experience in Data Science or 5+ years with a PhD in a relevant field (computer science, physics, mathematics, engineering).

5+ years of experience manipulating large data sets through SQL or Python

Experience with Neural Network and Natural Language processing (NLP) with large data sets.

2 years experience in big data technologies like Spark

Excellent understanding of machine learning techniques and algorithms

World’s Most Innovative Companies for 2023

Prepare reports for management stating trends, patterns, and predictions using relevant data.

Minimum Years of Experience: 3 in relevant field.

Experience with common data science toolkits such as R, SQL, and Python; familiarity with AI tools is an asset.

Experience with data visualization tools, such as Power BI, Tableau, Qlik Sense, etc.

In-depth knowledge of mathematics and statistics.

Excellent written and verbal communication skills and presentation skills.

Utilize data modeling and machine learning to optimize marketing campaigns, improve customer experience, and increase operational efficiency.

Competitive Salary $110,000 - $130,000 (based on experience)

THE ROLE: Data Scientist Entry level

Conduct A/B testing to optimize customer lifetime value (CLV) and reduce churn rate.

Apply advanced statistical and predictive modeling techniques to build, maintain, and improve upon multiple real-time decision systems.

Analyze large data sets using advanced Excel, SQL, and Python, identifying trends and informing business strategies.

3+ years of product-focused data science experience or equivalent

Experience performing data analysis and machine learning using Python or R

Experience using statistics to inform decision making

Experience with a BI tool such as Looker or Tableau

Experience with data warehouse design, development and best practices

Develop tools & resources to empower data access and self-service so your expertise can be leveraged where it is most impactful

Experience working with Machine Learning teams.

You have proven experience as a Data Scientist using experimentation methods and advanced statistical modeling to drive product development.

You have hands-on experience synthesizing insights from data using tools such as Python, R, BigQuery, SQL, Tableau.

Identify the most impactful opportunities for product development based on user needs, and execute on them diligently and resourcefully.

Define the metrics and dashboards we use to measure the health and success of our products.

Mentor and coach data scientists and tackle leadership opportunities within the larger data science community.

Develop and implement state-of-the-art algorithms and models that underpin AI features and capabilities.

Collaborate closely with engineering and product teams to comprehend requirements and translate them into effective AI features.

The candidate should have experience with modern machine learning and data science toolkits such as PyTorch/Tensorflow, Pandas, NumPy, Scikit-learn, Jupyter/Python.

Experience with training transformers, MLOps and tools such as SpaCy and Azure ML is a plus, as is experience with C#

Identify and source relevant structured and unstructured data from various internal and external sources.

Collect, preprocess, and transform data into usable formats, ensuring accuracy, completeness, and quality.

Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action

Establish metrics that measure the health of our products, as well as rider and driver experience

1-2 years of industry or project experience in solving data science or analytics problems

Experience in programming, especially with data science and visualization libraries in Python or R is helpful

Experience in statistical analysis (experience in online experimentation preferred)

Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners

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

Documentation Skills like drafting Technical Documentation, Business & System Requirements, PowerPoints

Add and operationalize incremental metrics related to new policy requirements, monitoring and oversight. 2.Operationalization of Chart of Accounts Policy (CCOA Policy)

Tracking registrations, attendance and pending to date. Manage module in dashboard on trainings assignments and completeness

Support ARCs discussions & requirements and reviewing new logic for ARCS data feed

Updating existing views – update parameters, refresh data to update existing modules, perform QC, optimize load time Business Knowledge

Knowledge of key terms & KPI’s related to policy, controls, governance and oversight activities & processes

Knowledge of optimization and predictive modeling techniques and experience applying them to real-world problems.

Minimum 2 Years Of Experience Required - Remote Position.

Partner with engineers, product managers, and business partners to identify algorithmic problems, brainstorm possible approaches, and recommend the best path forward.

Collaborate with stakeholders to prioritize projects and define requirements.

Skilled at translating a general question or problem into a clearly defined algorithmic solution.

Ability to work independently and manage multiple projects simultaneously.

Establish the life cycle management process for models.

Provide technical mentoring in modeling and analytics technologies, the specifics of the modeling process, and general consulting skills.

Experience in advanced analytics / data science technologies (e.g., machine learning, operations research, statistics, data mining)

Working knowledge of Microsoft Azure and tools in its ecosystem; proficiency in Python or R for data manipulation and analysis.

Experience solving problems with spatial autocorrelation and quantifying uncertainty using probabilistic algorithms is an asset.

Experience with data visualization tools.

Strong experience in data analysis, statistical modeling, and machine learning, with a focus on applying these skills to solve business problems

5+ years of analytics and data science experience or equivalent

Experience leading cross-functional projects and partnering with Product/Engineering/Marketing/Design on strategy and prioritization;

Experience with 0 to 1 products is a huge plus

Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning to research and produce insights

Coordinate and solve complex projects that extend beyond the traditional boundaries of product domains, analytics, and data science

Collaborate with cross-functional teams to understand project requirements and develop prototypes that meet those requirements

Test and iterate on prototypes to refine them and ensure they meet project goals and user needs

Document the prototyping process and provide clear instructions and specifications for handoff to development teams

Stay up-to-date with emerging technologies and trends, including machine learning and AI, and proactively identify opportunities for innovation and improvement.

Expertise in software development, hardware engineering, or another relevant field

Proficiency in programming languages such as Python, Java, or C++.

Technical knowledge regarding data models, database design development, data mining and segmentation techniques

Acquire , clean and structure data from various sources and maintain databases/data systems.

Identify , analyze, and interpret trends or patterns in complex data sets

Develop, prototype and test predictive algorithms

Filter and "clean" data, and review computer reports, printouts, and performance indicators to locate and correct code problems

Develop and implement data collection systems and other strategies that optimize statistical efficiency and data quality

Procure skills and knowledge on Python, Scikit-learn, Pandas, Numpy, Jupyter, PyTorch, Tensorflow, Matplotlib, Docker, AWS.

Basic understanding of Machine Learning concepts, and entry-level Python programming skills.

Applying your Machine Learning and Data Science skills to real practical problems from different industries.

All the candidates will be invited to complete a Skills Review Survey.

A problem solver, someone who enjoys challenges

A passion for learning and self-improvement