Data Scientist

About Joveo Joveo was founded in 2017 by a group of visionary entrepreneurs and enthusiastic problem solvers who foresaw the need for greater transparency and predictability in recruitment marketing. The focus was on building a cutting-edge technology platform that uses data and machine learning to enable employers, staffing agencies, RPOs, advertising agencies, and job sites to address this need better and more cost-effectively. We're the global leader in programmatic job advertising driving next-gen recruitment technology solutions for employers around the world. Harnessing machine learning and industry expertise, our platform delivers the most relevant candidates in the shortest time, giving our customers a competitive edge. Backed by marquee investors like Nexus Ventures Partners, Joveo has been featured in Inc. Magazine’s List of America’s Fastest-Growing Private Companies 2023. JOVEO stands for a job for everyone. That's our mission - to deliver the right job to everyone in the world. Powering more than twenty million jobs every day, we're changing the way recruitment media buying is done. This has never been more important. It’s not just about talent deployment – it’s about saving lives and families. Key Responsibilities: Execute the full Machine Learning lifecycle: feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop. Apply Supervised and Unsupervised Machine Learning techniques, including, Forecasting, Anomaly Detection, and Pattern Detection. Utilise a range of algorithms such as Decision Trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, and Deep Learning. Ensure compliance with regulatory standards for data handling and classification. Proficiency in SQL and relational databases, along with experience in Big Data technologies (Spark/Hadoop) and Cloud technologies. Conduct statistical and machine learning methods like A/B testing, experiment design, causal inference, and recommendation systems. Define and develop Key Performance Indicators (KPIs) and create reports to measure the impact of tests, content releases, and product improvements. Qualifications: Preferred PhD or Master’s degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field. Master's degree in Statistics, Economics, or a quantitative discipline, or equivalent practical experience is an added advantage. 4-6 years of experience as a statistician, or data scientist, including statistical data analysis with linear models, multivariate analysis, stochastic models, and sampling methods. Sound knowledge of ETL practices, preferably using Spark in Data Bricks or similar cloud big data technologies like Microsoft Azure or AWS. Experience with traditional and modern statistical techniques such as Regression, Support Vector Machines, Regularization, Boosting, Random Forests, and Ensemble Methods. Proficiency in analytical programming languages (Python or R) and SQL, along with experience in statistical software like R, Python, MATLAB, and pandas. Strong understanding of machine learning models, feature engineering, validation, scaling, deployment, and monitoring. Additional Skills: Ability to work independently and in a team environment. Strong problem-solving skills and attention to detail. Excellent communication and presentation skills. Proven track record of delivering high-quality data science solutions. Experience with programming languages for ETL operations and data analysis, including Python, Java, C++, and R. This job requires a blend of technical expertise, statistical knowledge, and strong analytical skills to drive predictive science initiatives effectively. If you meet these qualifications and are passionate about leveraging data for impactful insights, we encourage you to apply.