Spectrum is hiring for an entry level Associate Data Scientist role in US

Position:

• Associate Data Scientist

Company:

• Spectrum (Charter Communications, Inc.)

Location:

• Stamford, Connecticut, United States

Job type:

• Full Time

Job mode:

• Hybrid (combination of in-office and remote days)

Job requisition id:

• 2025-55213

Years of experience:

• 0-3 years (entry level)

Company description:

• Founded as a leading broadband connectivity company and cable operator, Spectrum (Charter Communications, Inc.) delivers services to more than fifty-seven million homes and businesses across forty-one states in the United States.

• Through its Spectrum brand families—Internet, TV, Mobile, Voice, Business, Enterprise, Reach and Networks—it offers an array of residential and commercial services, including high-speed internet access, digital video programming, voice telephony and mobile connectivity.

• By coupling a robust fiber-rich network with advanced telecommunications infrastructure, the company provides end-to-end solutions ranging from basic internet to customizable fiber-based offerings for large enterprises, government entities and educational institutions.

• With a workforce exceeding ninety thousand employees, the organization cultivates a culture that emphasizes innovation, collaboration and customer-centricity, empowering team members to deliver meaningful impacts in their communities.

• Spectrum’s business units span residential, small and medium business, enterprise, advertising and production, and specialized services for universities and healthcare, reflecting a diversified portfolio that drives resilience in an evolving digital landscape.

• The company invests heavily in research and development to remain at the forefront of next-generation 10G network platforms, supporting initiatives that integrate fiber, wireless and software-defined networking technologies.

• Spectrum’s reach is bolstered by its media production arm—Spectrum Networks—which distributes news, sports and original programming across multiple platforms, strengthening brand loyalty and engagement.

• Emphasizing a commitment to corporate social responsibility, Charter Communications partners with local communities, sponsoring educational programs, bridging the digital divide and supporting environmental sustainability efforts across service areas.

• The leadership team prioritizes diversity and inclusion, fostering an equitable workplace where employees from various backgrounds can contribute ideas, develop professionally and advance into leadership roles.

• Spectrum maintains rigorous data privacy and security protocols, ensuring customer information is protected in compliance with federal, state and local regulations.

• As part of its growth strategy, the company continually expands its high-speed internet footprint into underserved regions, aiming to narrow connectivity disparities and improve digital access for rural populations.

• For small and medium enterprises, Spectrum Business provides tailored bundles of broadband products, managed network solutions and cybersecurity services designed to enhance productivity and protect critical assets.

• Spectrum Enterprise focuses on designing and delivering large-scale fiber solutions, unified communications and cloud connectivity options for multinational corporations, educational campuses, healthcare networks and government organizations.

• Spectrum Reach operates as an advertising and production agency that leverages data analytics and targeted media placements to optimize brand exposure for clients across local and national markets.

• Commitment to employee well-being is evident through a comprehensive benefits package, which includes competitive compensation, healthcare plans, retirement savings options, tuition assistance, employee assistance programs and wellness incentives.

• Spectrum invests in continuous learning through internal training programs, tuition reimbursement, leadership development workshops and mentorship initiatives aimed at nurturing future leaders.

• The company implements inclusive recruitment practices, actively partnering with veteran organizations, minority-focused professional groups and university relations programs to attract diverse talent.

• Spectrum’s innovation labs foster cross-functional collaboration among engineers, data scientists, product managers and UX designers to prototype new products, iterate on customer feedback and accelerate time to market.

• In response to rapid technological change, the firm encourages employees to pursue certifications in cloud computing, network security, data engineering and AI to maintain a highly skilled workforce.

• Spectrum’s robust analytics ecosystem leverages tools such as Hadoop, Snowflake, Tableau, Alteryx and cloud services (AWS, Azure, GCP) to extract actionable insights that influence strategic decisions at all organizational levels.

• The social impact division partners with nonprofit organizations to provide low-cost internet connectivity to eligible households, advancing digital equity and enabling remote learning opportunities.

• Spectrum’s environmental initiatives include energy-efficient network upgrades, waste reduction efforts and adoption of renewable energy sources for data centers and office facilities.

• Through its Spectrum Charitable Foundation, the company provides scholarships, grant funding and volunteer opportunities to empower youth, veterans and underrepresented communities.

• The executive leadership promotes transparency by regularly communicating financial performance, strategic milestones and cultural initiatives to employees, shareholders and stakeholders through quarterly town halls.

• Spectrum has received industry recognition for its innovation, ranking among Fortune’s Most Innovative Companies and being acknowledged for best-in-class customer experience in independent surveys.

• As a publicly traded entity (NASDAQ: CHTR), Charter Communications prioritizes corporate governance, sustainability reporting and long-term shareholder value, driving accountability through a diverse board of directors.

• The company’s research and development center in Stamford serves as a high-tech hub where cross-disciplinary teams collaborate to solve challenges related to network scalability, latency reduction and emerging connectivity trends.

• Spectrum’s user-experience research team conducts regular user testing sessions, focus groups and surveys to inform product roadmaps, refine UI designs and streamline service delivery processes.

• Employee engagement is fostered through a variety of affinity groups—Women in Technology, Pride Alliance, Veterans Network—that provide networking, mentorship and advocacy for underrepresented populations within the organization.

• Through targeted campus recruiting and internship initiatives, Spectrum attracts top talent from leading universities, offering rotational programs that expose interns to data analytics, network engineering, marketing and finance.

• The company’s product and technology division recently launched pilot programs for 5G fixed wireless access, exploring opportunities to augment fiber offerings with next-gen wireless solutions for improved last-mile connectivity.

• Spectrum’s marketing organization leverages advanced segmentation models and predictive analytics to tailor messaging, optimize campaign ROI and personalize offers that drive subscriber growth and retention.

• The enterprise data warehouse integrates transaction, CRM and network performance data to support real-time dashboards, visualization tools and machine learning pipelines that empower business users.

• Spectrum’s legal and compliance teams monitor evolving telecommunications regulations, net neutrality policies and cybersecurity mandates to ensure the organization remains in full compliance and mitigates regulatory risk.

• The corporate finance division works closely with business units to forecast growth, allocate capital for network expansions and evaluate merger and acquisition opportunities that align with long-term strategic objectives.

• Spectrum’s talent acquisition team utilizes AI-driven screening tools to expedite candidate selection, reduce bias and enhance candidate experience through personalized communication and timely feedback.

• The company’s commitment to safety includes regular training programs, emergency preparedness drills and policies designed to protect employees in field operations, data centers and retail locations.

• Spectrum’s partnership with academic institutions supports joint research projects in areas such as data science, network optimization, cybersecurity and AI, fostering a pipeline of innovative solutions and future talent.

• Employees are encouraged to contribute to open source projects, publish research findings in industry journals and present at conferences, reinforcing Spectrum’s role as a thought leader in connectivity and data analytics.

• Spectrum’s vision is to remain at the forefront of the digital connectivity revolution by investing in emerging technologies, enhancing customer experiences and delivering reliable, high-quality services that connect communities.

Profile overview:

• As an Associate Data Scientist, you will work closely with seasoned data scientists and business partners to translate data into actionable insights that drive decision making across various departments.

• You will participate in the full analytics lifecycle, from understanding stakeholder requirements and formulating problem statements to collecting, cleaning, exploring and analyzing data in diverse formats (structured, semi-structured and unstructured).

• Your role will involve aggregating large volumes of data from multiple sources such as network logs, customer usage metrics, CRM systems, marketing databases and external market datasets to establish comprehensive data pipelines.

• You will leverage programming languages and data science toolkits—primarily Python or R—to implement statistical algorithms, build predictive models, conduct hypothesis testing and automate routine analyses.

• Under the guidance of senior data scientists, you will develop proficiency in machine learning techniques including regression, clustering, classification, time series forecasting and natural language processing, applying them to real-world business problems.

• You will assist in designing and implementing data quality checks, validation rules and anomaly detection procedures to ensure data integrity, consistency and accuracy across analytical workflows.

• Part of your responsibilities includes creating interactive visualizations and dashboards using tools such as Tableau, Power BI, Excel and Alteryx, enabling stakeholders to explore key performance indicators and monitor trends in near real time.

• You will support the development of scoring systems and ranking algorithms used in customer segmentation, churn prediction, lifetime value estimation and targeted marketing campaigns.

• Collaborating with cross-functional teams—marketing, operations, finance, customer experience—you will translate technical findings into concise, business-ready insights and recommendations to inform strategy and optimize processes.

• You will contribute to the documentation of data sources, modeling assumptions, algorithm configurations and validation metrics to maintain a robust knowledge base that ensures reproducibility and auditability.

• Your day-to-day work might include writing and optimizing SQL queries against data warehouses, retrieving and aggregating data, and delivering summary statistics or exploratory data analysis to inform hypothesis refinement.

• You will learn to leverage cloud-based infrastructures (AWS, Azure or Google Cloud) for scalable data processing, model training and deployment, using services such as S3, EC2, Lambda, Databricks or BigQuery.

• Under mentorship, you will explore opportunities to enhance existing analytics frameworks by integrating emerging tools—such as open source libraries, containerization (Docker) or orchestration platforms (Kubernetes)—to streamline model productionalization.

• You will support A/B testing and experimental design efforts to measure the impact of new product features, service changes or marketing initiatives, interpreting statistical results to recommend next steps.

• Your role involves collaborating on data governance initiatives, assisting in the definition of data stewardship policies, metadata standards and lineage tracking to ensure compliance with internal guidelines and external regulations.

• You will develop communication skills by presenting findings—via slide decks, whiteboard sessions or interactive dashboards—to audiences with diverse backgrounds, from technical peers to business leaders, tailoring your language accordingly.

• In conjunction with engineering and IT teams, you will participate in data architecture discussions—helping to identify new data sources, define schema requirements and improve ETL processes to enable more efficient analytics.

• You will learn best practices for model validation, cross-validation, hyperparameter tuning and performance tracking, ensuring that models meet accuracy, precision and recall benchmarks before moving toward production.

• The position encourages you to explore clustering techniques and unsupervised learning methods to reveal hidden customer segments, service usage patterns and operational inefficiencies that business stakeholders may not have considered.

• You will partner with data engineers and BI developers to deploy algorithms into production environments, monitoring model performance over time and retraining models as new data becomes available.

• You will assist in establishing key data correlations—linking network performance metrics with customer satisfaction scores or operational costs—to uncover opportunities for service enhancements or cost reductions.

• Your role includes supporting root cause analysis by using techniques such as decision trees, random forests or gradient boosting machines to identify factors driving customer churn or network downtime.

• You will gain exposure to advanced analytics technologies—like deep learning frameworks (TensorFlow, PyTorch)—and evaluate their suitability for solving complex problems such as image analysis, anomaly detection or speech recognition.

• The position emphasizes learning about feature engineering best practices—creating new variables, handling missing values, encoding categorical variables and scaling numeric features—to improve model robustness and generalizability.

• You will refine your ability to identify and interpret patterns within time series data—such as network usage spikes or seasonal customer behavior—leveraging techniques like ARIMA, Prophet or LSTM networks.

• You will contribute to the continuous improvement of analytics processes by conducting retrospectives on completed projects, documenting lessons learned and proposing enhancements to methodologies, tools or collaboration workflows.

• On a typical day, you might join brainstorming sessions with marketing to clarify how predictive models could optimize targeted promotions, then switch to writing code that analyzes campaign performance metrics.

• You will assist in preparing executive summaries and infographics that synthesize complex analytical findings into clear, digestible formats for leadership review.

• Through hands-on experience, you will develop an understanding of network infrastructure—learning how data is generated along the connectivity stack (from physical hardware to last-mile connectivity) and how it can be harnessed for predictive maintenance or capacity planning.

• You will be part of a high-energy, collaborative environment where your contributions help reinforce Spectrum’s commitment to data-driven decision making, continuous innovation and exceptional customer experiences.

• Over time, you will expand your technical repertoire to include containerization (Docker), workflow orchestration (Airflow), CI/CD pipelines for models and version control best practices (Git, GitHub) to support end-to-end analytics projects.

• Your participation in weekly team knowledge-sharing sessions and code reviews will facilitate rapid upskilling, enabling you to progress from foundational analytics tasks to leading your own mini-projects under senior guidance.

• You will experience a growth trajectory where you start by tackling smaller analysis tasks—such as measuring campaign ROI—and gradually take on more complex assignments like building end-to-end machine learning workflows.

• In this role, you become an integral part of Spectrum’s mission to deliver accurate, timely insights that empower business units to adapt quickly to market changes, optimize operational efficiency and improve customer satisfaction.

Qualifications:

• Bachelor’s degree in Computer Science, Statistics, Operations Research or a related quantitative discipline, or equivalent combination of education and hands-on experience.

• Demonstrated exposure to data analytics workflows—such as gathering requirements, data grooming, exploration and communication of insights—through academic projects, internships or entry-level positions.

• Basic proficiency in Python or R, with knowledge of core libraries (pandas, numpy, scikit-learn, tidyverse, ggplot2) for data manipulation, visualization and model development.

• Foundational SQL skills, including writing SELECT statements, JOINs, GROUP BY clauses and basic window functions to query relational databases for data extraction and aggregation.

• Minimal experience using analytical and statistical software (SAS, SPSS, Stata or similar) to perform exploratory data analysis, summary statistics and hypothesis testing.

• Familiarity with data visualization tools—Tableau, Power BI, Qlik or equivalent—to create interactive dashboards and present key performance indicators in a user-friendly format.

• Exposure to Alteryx, KNIME or comparable ETL/analytics platforms for designing repeatable data workflows, preparing datasets and automating data processing tasks.

• Understanding of core computer science principles, including algorithmic complexity, data structures (arrays, lists, dictionaries, trees) and software design methodologies (OOP, functional programming).

• Prior exposure to cloud-based infrastructures (AWS, Azure or GCP) and services such as S3, EC2, Lambda or BigQuery, enabling you to participate in scalable data processing and model training.

• Basic knowledge of statistical techniques—such as regression analysis, correlation analysis, hypothesis testing (t-tests, chi-square tests) and descriptive statistics (mean, median, standard deviation).

• Familiarity with introductory machine learning concepts—supervised vs. unsupervised learning, overfitting vs. underfitting, model evaluation metrics (accuracy, precision, recall, F1 score).

• Effective analytical and problem-solving skills, demonstrating attention to detail in data cleaning, validation and interpretation of statistical results to ensure accuracy and reliability.

• Ability to read, write and speak English fluently, enabling you to develop clear documentation, compose technical reports and present findings to diverse audiences.

• Strong interpersonal communication skills—both verbal and written—to collaborate with team members, build relationships with stakeholders and provide customer-oriented service in fast-paced environments.

• Aptitude for performing in-depth research and analysis using academic literature, industry reports and online resources to inform modeling approaches or validate assumptions.

• Demonstrated ability to maintain confidentiality and handle sensitive information in accordance with company policies, data governance standards and regulatory requirements.

• Capacity to work effectively in a team setting, adapt to shifting priorities and manage multiple tasks while meeting defined project deadlines.

• Detail-oriented mindset, with a commitment to data accuracy, reproducibility and thorough documentation of methodologies, code and results.

• Familiarity with version control systems (Git, GitHub) to manage code repositories, track changes and collaborate on shared projects.

• Knowledge of fundamental cloud security principles—identity and access management, encryption, network security—to support secure deployment of analytics solutions in cloud environments.

• Experience with basic statistical data quality procedures—such as missing data imputation, outlier detection and consistency checks—to ensure reliability of analyses and reduce bias in modeling.

• Exposure to or understanding of A/B testing frameworks, experiment design considerations (sample size, control vs. treatment groups), and analysis of test results to derive meaningful conclusions.

• Awareness of data governance concepts—metadata management, data lineage, stewardship roles—enabling you to contribute to cross-functional initiatives that strengthen data reliability.

• Familiarity with business intelligence platforms, data warehousing concepts (star schema, snowflake schema), ETL processes and dimensional modeling to support structured data environments.

• Prior exposure to scripting languages (Bash, PowerShell) or automation tools (Airflow) to schedule routine data tasks and orchestrate end-to-end data pipelines.

• Understanding of network operations, telecommunications terminology and key performance metrics (latency, throughput, packet loss), which can help contextualize data within Spectrum’s infrastructure.

• Ability to collaborate with data engineers, BI developers and IT operations teams to deploy statistical algorithms into production, monitor performance and troubleshoot issues.

• Prior experience or strong inclination toward continuous learning, actively seeking out tutorials, online courses or workshops to build new skills in data science and emerging technologies.

• Willingness to work in a hybrid environment, adhering to in-office schedules when required and maintaining productivity on remote days, demonstrating self-discipline and strong time management.

• Travel ability: Primarily office-based in Stamford, Connecticut, with occasional travel to other Spectrum locations for team meetings, training sessions or conferences if needed.

• Preferred: Internship experience in a data science role where you contributed to building models, generating analytical reports or collaborating on cross-functional analytics projects under guidance.

• Preferred: Participation in academic competitions (Kaggle, college hackathons, math contests) or involvement in open source analytics initiatives that demonstrate practical application of data science skills.

• Preferred: Coursework or certifications in machine learning, cloud computing, big data technologies or data visualization from accredited institutions, online platforms or professional organizations.

• Preferred: Basic understanding of data privacy regulations (GDPR, CCPA) and best practices for handling personally identifiable information to ensure compliance within analytics processes.

• Preferred: Exposure to agile methodologies (Scrum, Kanban) and familiarity with project management tools (Jira, Trello, Asana) to contribute to iterative development cycles and cross-team collaboration.

• Preferred: Prior experience using Git-based branching strategies, pull request reviews and collaborative workflows to support team-oriented code development and quality control.

• Preferred: Experience with Jupyter notebooks or RStudio as interactive computing environments for exploratory data analysis, documentation and sharing reproducible code.

• Preferred: Engagement in professional associations (INFORMS, IEEE, ACM) or local meetups that focus on data science, analytics or machine learning, demonstrating commitment to professional growth.

• Preferred: Basic knowledge of natural language processing (NLP) techniques—such as tokenization, sentiment analysis, named entity recognition—that could support future text analytics projects.

• Preferred: Familiarity with containerization tools (Docker) or orchestration platforms (Kubernetes) to support deployment of models and scalable cloud-native analytics solutions.

• Preferred: Experience creating technical documentation (README files, wikis, standard operating procedures) to support knowledge transfer and maintain project transparency.

• Preferred: Understanding of fundamental DevOps principles—continuous integration, continuous delivery, automated testing—to support seamless integration of analytics workflows into production environments.

Additional info:

• As an Associate Data Scientist, your work directly influences Spectrum’s ability to make data-driven business decisions, enhancing customer experience, optimizing network operations and improving profitability across business units.

• You will be part of a forward-thinking Business Intelligence team that values collaboration, innovation and long-term career growth, providing a supportive environment where continuous improvement is encouraged.

• The hybrid work model allows for flexibility—enabling you to collaborate in person with colleagues on data workshops, brainstorming sessions and code reviews while also affording remote days for focused analysis and learning.

• You will benefit from mentorship by seasoned data scientists who will invest time in your professional development, guiding you through model design, code best practices and effective stakeholder communication.

• Spectrum fosters a culture that balances high-energy project work with strong respect for work-life harmony, offering resources such as flexible scheduling, employee assistance programs and wellness initiatives.

• You will have access to advanced analytics tools and platforms, including Tableau, Alteryx, Python libraries, R packages and cloud resources, enabling you to experiment with new methodologies and prototype solutions rapidly.

• The role emphasizes continuous learning—Spectrum provides tuition reimbursement, internal training programs, access to online learning platforms (Coursera, Udacity, edX) and opportunities to earn industry certifications in data science, cloud computing and related areas.

• You will receive structured feedback through regular performance reviews, one-on-one meetings with your manager and participation in peer code review sessions to ensure consistent progress in technical and interpersonal competencies.

• As part of the onboarding process, you will be introduced to Spectrum’s data governance framework, learning how data stewardship, privacy standards and regulatory compliance shape analytics initiatives across the organization.

• You will engage with cross-functional teams—marketing, finance, operations, product—to help translate business questions into analytic use cases, fostering a holistic understanding of Spectrum’s ecosystem.

• The role includes opportunities to support community-oriented projects, volunteering for Spectrum’s charitable initiatives—such as digital literacy programs in underserved schools or network expansions for community centers.

• You will be part of an employee resource network that hosts regular meetups, lunch-and-learn sessions and hackathon events, allowing you to connect with peers who share interests in data science, engineering or network technology.

• The compensation package is competitive for entry-level positions in the analytics field, including base salary, performance-based bonuses and eligibility for stock unit awards tied to company performance.

• Spectrum provides comprehensive healthcare benefits—medical, dental, vision—and supports mental health wellness through counseling services, stress management workshops and wellness reimbursements.

• You will be enrolled in Spectrum’s retirement savings plan (401(k)), with company matching contributions and resources for retirement planning to help secure your long-term financial future.

• The company offers generous paid time off policies—including vacation, personal days and sick leave—as well as paid parental leave, holiday pay and bereavement leave, supporting your life outside of work.

• You will gain exposure to senior leadership through quarterly town halls, “Ask Me Anything” sessions and leadership roundtables where executives share strategic priorities, financial results and address employee questions.

• The role may involve attending analytics conferences, internal hackathons or skill-building workshops sponsored by Spectrum, providing opportunities to network with industry professionals and broaden your knowledge.

• You will collaborate with a team that values inclusivity and diversity, participating in Spectrum’s employee resource groups (Women in Tech, Veterans Network, Pride Alliance) to share experiences and advocate for equitable policies.

• You can leverage Spectrum’s internal mobility programs to explore lateral moves into data engineering, business analysis or product management roles as your interests and skills evolve.

• The organization celebrates innovation—if you propose and execute a successful proof of concept that drives measurable business value, you may be recognized through Spectrum’s innovation awards program.

• You will be encouraged to publish technical blogs or present findings at internal Brown Bag sessions, strengthening your communication skills and contributing to Spectrum’s knowledge-sharing culture.

• Spectrum’s total rewards program includes wellness incentives, fitness reimbursements and employee discounts on Spectrum services, enabling you to experience the products and services you help improve.

• The company provides relocation assistance for candidates moving to Stamford, Connecticut, including a one-time relocation stipend, temporary housing recommendations and local area orientation.

• You will join a team that consistently receives high marks for employee engagement, with regular surveys informing leadership about areas for improvement and recognizing top team achievements.

• You will benefit from structured career path planning—Spectrum offers clear progression tracks for analytics professionals, outlining competencies needed to advance from Associate Data Scientist to Data Scientist, Senior Data Scientist and Leadership roles.

• Spectrum embraces agile methodologies; you will participate in sprint planning, stand-ups and retrospectives as part of a cross-functional analytics squad that iterates rapidly on data products and solutions.

• The role will provide exposure to compliance requirements—learning how to navigate telecommunications regulations, net neutrality guidelines and data privacy laws that impact analytics deliverables.

• You will collaborate with the network operations team to develop predictive maintenance models that identify potential service outages, leveraging time series analysis and anomaly detection to minimize downtime.

• You will assist marketing teams by analyzing campaign performance, building response models that optimize budget allocation and recommending segmentation strategies to improve customer acquisition and retention.

• Your contributions to churn prediction efforts will help the customer experience organization identify at-risk subscribers, enabling targeted retention offers and personalized engagement tactics.

• As part of the enterprise analytics initiative, you will support revenue optimization projects, analyzing pricing strategies, discount efficacy and bundling options through advanced statistical modeling.

• You will explore use cases for natural language processing—such as analyzing customer service transcripts or social media sentiment—to uncover service pain points and inform product enhancements.

• You will help the finance team develop forecasting models for revenue, costs and capital expenditures, applying time series methods and scenario analysis to drive more accurate budgeting.

• You will collaborate with cybersecurity teams to identify patterns of fraudulent activity, using clustering and outlier detection to flag suspicious network traffic or anomalous user behaviors.

• The position offers exposure to advanced topics such as reinforcement learning, deep neural networks and graph analytics, allowing you to explore cutting-edge methods under senior mentorship.

• You will be assigned project goals with clear deliverables and timelines, practicing effective time management, proactive status reporting and risk escalation when necessary to keep projects on track.

• You will participate in code review processes, receiving constructive feedback on code quality, documentation practices and adherence to coding standards that ensure maintainability and collaboration.

• As an entry-level data scientist, you will have a unique opportunity to shape your career trajectory—Spectrum supports internal certifications, attendance at data science conferences and membership in professional organizations to foster continuous growth.

• You will gain a comprehensive understanding of how data analytics supports Spectrum’s broader mission to keep communities connected, drive operational excellence and create exceptional customer experiences through data-informed strategies.

Please click here to apply.

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