<p> Analyst, Talent Analytics (Machine Learning)<br /> <br /> We are seeking a highly skilled and analytically driven Talent Analyst with a specialized focus on Machine Learning for our Talent Acquisition Analytics team. In this pivotal role, you will apply advanced data science and machine learning techniques to optimize every stage of our talent acquisition lifecycle, from sourcing to forecasting hiring needs and improving/understanding the quality of hire. You will also be responsible for querying relevant data and running various statistical analyses to better understand the performance of our hiring process.<br /> <br /> Key Responsibilities:<br /> • Predictive Model Development for Talent Acquisition: Design, develop, train, validate, and deploy machine learning models to predict key talent acquisition outcomes. This includes, but is not limited to:<br /> • Candidate Success Prediction: Building models to forecast candidate performance, retention, and cultural fit based on various pre-hire data points.<br /> • Sourcing Channel Optimization: Developing models to identify the most effective and efficient sourcing channels for different roles and demographics.<br /> • Time-to-Hire & Cost-per-Hire Forecasting: Creating predictive models to estimate hiring timelines and associated costs, enabling better resource allocation.<br /> • Flight Risk/Retention Analysis (pre-hire indicators): Identifying early indicators in the talent acquisition process that may correlate with future retention or attrition.<br /> • Talent Funnel Optimization & Anomaly Detection: Analyze large datasets from Applicant Tracking Systems (ATS), HRIS, and other recruitment platforms to identify bottlenecks, biases, and areas for improvement in the talent acquisition funnel.<br /> • Research & Analysis: Design and execute statistical tests to evaluate the impact of various elements of the recruitment process. Analyze results to provide actionable recommendations.<br /> • Workforce Planning & Demand Forecasting: Develop models to forecast future talent demand, identify skill gaps, and inform long-term workforce planning strategies.<br /> • General Reporting: Develop and execute SQL queries to extract data from various databases for reporting and analysis.<br /> Required Qualifications:<br /> • Education: Degree in Data Science, Computer Science, Statistics, Mathematics, Industrial-Organizational Psychology (with strong quantitative focus), or a related quantitative field.<br /> • Experience: 2-4 years of hands-on professional experience as a Data Scientist or Advanced Analytics, with a significant portfolio of machine learning projects, ideally within the HR or Talent Acquisition domain.<br /> • Programming: Strong proficiency in R or Python for data manipulation, statistical analysis, and machine learning model development.<br /> • Machine Learning Expertise: Deep understanding and practical experience with a wide range of supervised and unsupervised machine learning algorithms relevant to predictive modeling, classification, regression, and clustering.<br /> • Statistical Modeling: Strong foundation in statistical inference, hypothesis testing, experimental design, time series analysis, and causal inference.<br /> • Data Querying & Databases: Proficient in SQL for extracting and transforming data from complex relational databases (e.g., HRIS, ATS). Experience with large-scale data warehouses.<br /> • Communication & Storytelling: Exceptional ability to translate complex analytical findings and technical concepts into clear, concise, and actionable recommendations for non-technical audiences, including senior executives.<br /> This role can be remote within the US or onsite at our offices in Los Gatos, Los Angeles, or New York.<br /> Our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $80,000 - $280,000.<br /> Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more detail about our Benefits here.<br /> Netflix is a unique culture and environment. Learn more here.<br /> Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.<br /> We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.<br /> Job is open for no less than 7 days and will be removed when the position is filled.<br /> <p id='jobcode'>Jobcode: Reference SBJ-744b2p-172-68-234-116-42 in your application.</p> </p>