Senior/Lead Data Scientist (Python, SQL, ML, Spark)

Company InformationFounded in 2018, Data Nest is a dynamic and innovative company specialising in credit scoring, lead generation services and other products. By harnessing the power of Data Analytics and AI, we help finance companies to reduce their credit loss, to widen their consumer base, and to fasten their release of new financial services.We aim to transform the financial landscape through the strategic application of data analytics and AI and make a better society where financial services are accessible for everyone.Are you ready to be part of a dynamic and passionate team at the forefront of revolutionising the financial industry? Look no further – Data Nest is the place to be!Why Choose Data Nest?Market-Leading Benefits:At Data Nest, we believe that our success is fueled by the talent and dedication of our team members. That's why we're proud to offer top-notch benefits that set us apart from the rest!Innovation at its Core: We're not just another company; we're a hub of innovation, where your ideas are valued, and your creativity is encouraged.Exciting Challenges: We tackle challenges head-on and view them as opportunities for growth. Join us in solving complex problems and pushing the boundaries of what's possible in the world of data analytics and AI.Apply now - Your future start here !A. JOB DESCRIPTIONWe are looking for innovative data scientists to build and evolve our leading financial products. You will work with a team of young and talented scientists and engineers to build robust and scalable data models using big data pipelines, conduct advanced research in implementing state-of-the-art ML and AI techniques, build high-quality data services that are both real-time and batch-based.B. RESPONSIBILITIESDevelop our extensive range of products such as Credit Score, Fraud Score, Income Score, Lead Generation, etc.Utilize robust Big Data platform and powerful computation clusters to perform your day-to-day tasks of analysis, modeling, feature engineering, deployment and monitoring.Work with broad categories of structured and unstructured data such as tabular, text, media, etc. to improve ML models.Experience full MLOps practices: streamlined data pipeline, deployment, feature monitoring, model performance monitoring, business integration.Mentor Junior Data Scientists and provide them with practical guidance, as needed.Partner with business stakeholders to translate business challenges into data science projects with measurable outcomes.Communicate insights effectively to both technical and non-technical stakeholders.Define team goals, manage project timelines, and ensure delivery of high-quality, business-impactful outcomes.Collaborate cross-functionally teams to align data science initiatives with company strategy.Drive adoption of best practices, innovation, and continuous improvement within the Data Science team