{"id":2910590,"url":"https://alion.io/job/amd-data-scientist-sales-operations-2","title":"Data Scientist (Sales Operations)","company":{"id":93,"name":"AMD","domain":"amd.com","url":"https://alion.io/company/amd","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Jibe","truth_index":{"grade":"B","score":80,"open_postings":157,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":107000,"max_usd":203000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":479},"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Bash","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"Matplotlib","optional":false},{"name":"Plotly","optional":false},{"name":"Prophet","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Seaborn","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false},{"name":"Unix","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-10-02T18:23:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-22T11:40:18Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"WHAT YOU DO AT AMD CHANGES EVERYTHING\nAt AMD, our mission is to build great products that accelerate next-generation computing experiences-from AI and data centers, to PCs, gamingand embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuityand a shared passion to create something extraordinary. When you join AMD, you’lldiscover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges-striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.Together, we advance your career.\nTHE ROLE:\nWe are seeking a highly skilled Data Scientist to lead initiatives in advanced analytics, predictive modeling, and generative AI for our Sales Operations org. This role combines statistical expertise, machine learning, and cutting-edge generative models to deliver actionable insights that drive strategic decisions across multiple business areas. As part of our team, you will collaborate with cross-functional teams to optimize revenue, improve operations, and empower sales and marketing professionals by leveraging data-driven solutions and AI to minimize manual tasks, enabling them to focus more efficiently on selling products.\nTHE PERSON:\nThe person we are looking for should have passion in data science. He/she has strong SQL and programming skills (Python is preferred) and has a good understanding of statistics and machine learning algorithms.\nKEY RESPONSIBILITIES:\n Predictive Modeling & Machine Learning:\nDevelop and deploy predictive models using machine learning algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast.\nBuild end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability.\nTime-Series Forecasting:\nCreate robust time-series forecasting models for revenue, demand, and operational metrics using techniques like ARIMA, Prophet, Bayesian methods, and hybrid approaches.\nPartner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes.\n Generative AI & Advanced Analytics:\nDesign and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems.\nData Pipeline & Infrastructure:\nCollaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting.\nLeverage big data frameworks (e.g., Snowflake, Hadoop, Spark) for efficient data processing and storage.\nExploratory Data Analysis & Visualization:\nPerform exploratory data analysis to uncover patterns and insights from structured and unstructured data sources.\nDevelop visualizations using tools such as Plotly, Matplotlib and Seaborn to communicate findings effectively to stakeholders.\nCollaboration & Impact Measurement:\nWork closely with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions.\nMonitor model performance post-deployment and iterate on models to ensure continued business impact.\nContinuous Learning & Innovation:\nStay updated on emerging technologies in AI, machine learning, and generative models.\nExperiment with new tools and techniques to enhance team capabilities and drive innovation.\nQUALIFICATIONS:\n Education:Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.\n\n Technical Skills:\nProficiency in Python, SQL, and other programming languages.\nStrong understanding of machine learning algorithms and statistical techniques.\nHands-on experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and frameworks for generative AI.\nFamiliarity with time-series forecasting methods and tools.\nExperience working with big data technologies (e.g., Snowflake, Hadoop, Spark).\nBasic knowledge of UNIX shell scripting (Bash, Zsh).\nExperience:\nMinimum of 3+ years of experience in data science or related fields.\nDemonstrated ability to deliver end-to-end ML projects from start to finish.\nExperience with version control tools like Git and GitHub.\nBusiness Acumen:\nAbility to translate technical insights into actionable business strategies.\nStrong communication skills to effectively collaborate with cross-functional teams.\nThis role is not eligible for visa sponsorship.\nLOCATION:\nAustin, TX\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers and will consider all applicants without regard to race, marital status, sex, age, color, religion, national origin, veteran status, disability or any other characteristic protected by law. EOE/MFDV\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.\n\nThis posting is for an existing vacancy.\nTHE ROLE:\nWe are seeking a highly skilled Data Scientist to lead initiatives in advanced analytics, predictive modeling, and generative AI for our Sales Operations org. This role combines statistical expertise, machine learning, and cutting-edge generative models to deliver actionable insights that drive strategic decisions across multiple business areas. As part of our team, you will collaborate with cross-functional teams to optimize revenue, improve operations, and empower sales and marketing professionals by leveraging data-driven solutions and AI to minimize manual tasks, enabling them to focus more efficiently on selling products.\nTHE PERSON:\nThe person we are looking for should have passion in data science. He/she has strong SQL and programming skills (Python is preferred) and has a good understanding of statistics and machine learning algorithms.\nKEY RESPONSIBILITIES:\n Predictive Modeling & Machine Learning:\nDevelop and deploy predictive models using machine learning algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast.\nBuild end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability.\nTime-Series Forecasting:\nCreate robust time-series forecasting models for revenue, demand, and operational metrics using techniques like ARIMA, Prophet, Bayesian methods, and hybrid approaches.\nPartner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes.\n Generative AI & Advanced Analytics:\nDesign and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems.\nData Pipeline & Infrastructure:\nCollaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting.\nLeverage big data frameworks (e.g., Snowflake, Hadoop, Spark) for efficient data processing and storage.\nExploratory Data Analysis & Visualization:\nPerform exploratory data analysis to uncover patterns and insights from structured and unstructured data sources.\nDevelop visualizations using tools such as Plotly, Matplotlib and Seaborn to communicate findings effectively to stakeholders.\nCollaboration & Impact Measurement:\nWork closely with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions.\nMonitor model performance post-deployment and iterate on models to ensure continued business impact.\nContinuous Learning & Innovation:\nStay updated on emerging technologies in AI, machine learning, and generative models.\nExperiment with new tools and techniques to enhance team capabilities and drive innovation.\nQUALIFICATIONS:\n Education:Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.\n\n Technical Skills:\nProficiency in Python, SQL, and other programming languages.\nStrong understanding of machine learning algorithms and statistical techniques.\nHands-on experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and frameworks for generative AI.\nFamiliarity with time-series forecasting methods and tools.\nExperience working with big data technologies (e.g., Snowflake, Hadoop, Spark).\nBasic knowledge of UNIX shell scripting (Bash, Zsh).\nExperience:\nMinimum of 3+ years of experience in data science or related fields.\nDemonstrated ability to deliver end-to-end ML projects from start to finish.\nExperience with version control tools like Git and GitHub.\nBusiness Acumen:\nAbility to translate technical insights into actionable business strategies.\nStrong communication skills to effectively collaborate with cross-functional teams.\nThis role is not eligible for visa sponsorship.\nLOCATION:\nAustin, TX\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers and will consider all applicants without regard to race, marital status, sex, age, color, religion, national origin, veteran status, disability or any other characteristic protected by law. EOE/MFDV\nBenefits offered are described: AMD benefits at a glance.\nAMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.\nAMD may use Artificial Intelligence to help screen, assess or select applicants for this position. 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