Data Scientist / Machine Learning Engineer

Job Description

Roles and Responsibilities Design, develop, and deploy machine learning models using various algorithms such as Bayesian statistics, frequentist statistics, optimization techniques, time series analysis, reinforcement learning, NLP, etc. Collaborate with stakeholders to understand business requirements and translate them into data science solutions. Develop high-quality code in Python (Pandas, NumPy, Matplotlib) or R (base packages) for building ML models. Ensure scalability and efficiency of deployed models by monitoring performance metrics like accuracy, precision, recall etc. Communicate complex technical insights effectively through reports and presentations. Desired Candidate Profile 4-8 years of experience in Data Science/Machine Learning Engineering with a strong background in finance/risk domain. Bachelor's degree in Any Specialization (B.Sc/B.Tech/B.E.). Proficiency in programming languages like Python/R; familiarity with cloud platforms like GCP/AWS/Azure; experience with big data tools like Spark/Hadoop. JD DETAILS- Data Scientist / Machine Learning Engineer - Neo soft client looking for candidates who are good in building ML Models for Financial/Risk verticals. make sure candidates have enough experience in building models. Job Title: Data Scientist / Machine Learning Engineer Experience: 4 Years Location: Bangalore (Lingarajapuram) Budget: 18 LPA What Youll Do You will work directly as part of AA CoE and be a part of analytics focused projects across statistics, optimization & simulations, machine learning and Big Data. Your role will involve design and implementation of advanced statistical analysis and machine learning algorithms to derive business insights and solve complex business problems. This includes gathering and analyzing information, formulating and testing hypotheses, and developing and communicating recommendations. You may also be responsible for presenting results to management and implementing recommendations with team members. You’ll have the opportunity to gain new skills and build on the strengths you bring to the company. Main task Design and implement machine-learning models to support the business’s numerous initiatives and programs with a view of achieving overall objectives and targets Successful documentation of reusable code Achieve personal technical development and learning goals Conduct knowledge sharing sessions internally within the CoE as well as externally in meetups, conferences etc. Participate in and help plan cultural initiatives for CoE Qualifications University degree in Computer Science, Engineering, Applied Mathematics or related fields and excellent academic record required; Master’s degree in above mentioned subjects preferred 4 years of technical experience in handling large datasets and applying advanced statistical and machine learning algorithms Hand-on experience in methodologies such as: Supervised and Unsupervised Learning, Feature Engineering, Bayesian Statistics, Frequentist Statistics, Optimization, Time Series, Graph/Network Theory, Reinforcement Learning, Deep Learning, Computer Vision, NLP, Interpretable AI, etc. Proficiency with at least one of the following languages: R, Python, SAS and experience of working with SQL/NoSQL databases Experience of working on platforms such as GCP, Dataiku, AWS, Azure, etc. Stakeholder management skills with ability to communicate and work with senior management effectively Skills to communicate complex ideas effectively