4 Supervised Ml Jobs

As a part-time Data Scientist with over 4 years of experience, you will be responsible for building the Machine Learning foundation for a high-velocity US-focused startup. The position offers approximately 3 months of work initially, with the potential for a full-time role requiring 12 hours per week. It is important to note that Data Analytics is distinguished from Data Science. Inveno, a New York City-based startup, aims to automate the manual resource planning processes that occur daily at warehouses across the United States. The current problem being addressed is the reliance of 75% of US warehouses on manual shift planning, leading to inefficiencies amounting to over $1 million per warehouse annually. By utilizing operational data and developing custom AI and optimization models, Inveno seeks to assist warehouse managers in planning with precision, speed, and scalability. The founding team behind Inveno consists of a warehouse operations expert with 8 years of experience, a CEO with a successful track record of building and exiting companies, and a CTO experienced in scaling engineering and systems across various ventures globally. The company has made significant progress, with the V1 product set to go live with the first client in 2 months. Inveno has also secured a paid contract with a global multi-brand conglomerate and has a promising pipeline with some of the largest retailers in the US. As a Data Scientist in this role, you will be responsible for leading the development of the optimizer, building machine learning models, collaborating on the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing core optimization engines, creating supervised learning models, designing workflows, and setting up model versioning and deployment pipelines. Qualifications and skills required for this position include experience in designing and deploying constraint-based optimization models, advanced Python skills, a strong foundation in supervised machine learning, the ability to translate complex operational problems into solvable models, and a degree in Computer Science, Operations Research, Statistics, or a related quantitative field.,

As a part-time Data Scientist with more than 4 years of experience, you will have the opportunity to build the machine learning foundation for a high-velocity US-focused startup. The position involves approximately 3 months of work initially, with the potential for full-time engagement (12 hours per week). Inveno, a New York City-based startup, is dedicated to automating the manual resource planning processes that occur daily in US warehouses. The primary problem being addressed is the prevalent manual shift planning in 75% of US warehouses, leading to inefficiencies costing over $1 million annually per warehouse. By leveraging operational data and developing custom AI and optimization models, Inveno aims to empower warehouse managers with precise, efficient, and scalable planning solutions. The founding team of Inveno consists of three members: - A warehouse operations expert with 8 years of experience at prominent logistics startups in the US and India. - A CEO with a track record of building and exiting three companies, as well as leading teams at Alibaba Group. - A CTO experienced in scaling engineering and systems across various international ventures. In terms of progress, Inveno's V1 product is scheduled to go live with the first client within 2 months. The startup has already secured a paid contract with a global multi-brand conglomerate and has a promising pipeline including some of the largest retailers in the US. As a data scientist joining the team, you will play a crucial role in leading the development of the core optimization engine, building machine learning models to support the optimizer, shaping the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing the core optimization engine, creating and deploying supervised learning models, collaborating with engineering on workflow design, and setting up model versioning, deployment, monitoring, and experimentation pipelines. Qualifications & Skills Required: - Experience in designing and deploying constraint-based optimization models using tools like Google OR-Tools, Gurobi, CPLEX, or similar. - Proficiency in advanced Python skills and familiarity with the data science stack including NumPy, pandas, and scikit-learn. - Strong foundation in supervised machine learning, encompassing feature engineering, model selection, and validation techniques. - Demonstrated ability to translate complex operational problems into solvable mathematical or machine learning models. - Bachelor's or Master's degree in Computer Science, Operations Research, Statistics, or a related quantitative field. Joining Inveno as a Data Scientist presents a significant opportunity for career advancement by taking ownership of the development and deployment of a foundational model that drives innovation in a critical sector.,

We are currently seeking a highly-skilled Data Science Senior Manager with a strong background in data analytics and management. The ideal candidate will have a proven track record of leveraging data-driven insights to drive business improvement and optimize overall business performance. You should have a minimum of 10-14 years of relevant experience in the field of Data Science. As a Data Science Senior Manager, your key responsibilities will include managing and leading a team of data scientists to achieve organizational goals, driving the collection, cleaning, and preprocessing of complex datasets, building predictive models and machine-learning algorithms, proposing solutions and strategies to business challenges, collaborating with engineering and product development teams, overseeing the development and implementation of ML algorithms and models, utilizing predictive modeling to increase and optimize customer experiences, revenue generation, campaign optimization, and other business outcomes, identifying valuable data sources and automating collection processes, undertaking data collection, preprocessing, and analysis, and communicating complex data or algorithms into insights that everyone can understand. You should have proficiency in SQL, Python, Pyspark, experience in data pre-processing, deep knowledge of Supervised ML, EDA, Unsupervised ML, strong understanding of Forecasting Algorithms, Ensemble Models, Causal approaches, excellent understanding of machine learning algorithms, processes, tools, and platforms, proven experience as a Data Science Manager or similar role, strong problem-solving and analytical skills, good communication skills with the ability to explain complex concepts to non-technical stakeholders, and strong leadership and project management skills. Qualifications should include a Bachelor's Degree in Computer Science, Statistics, Applied Math, or a related field with a Master's Degree preferred, and a minimum of 10-14 years of experience in data science or a related field. This is an excellent opportunity for individuals looking to apply their leadership and technical skills in a dynamic and fast-paced environment. We are an equal opportunity employer and value diversity and inclusion at our company. We encourage applications from all backgrounds. If you are passionate about data science and are eager to make a significant impact within a leading organization, apply today. Join us and be a part of our exciting journey.,

As a member of the Classical ML+NLP+Gen AI - L4 team at Tredence, you will be involved in tasks such as Model Fine-tuning, Model Pre-training, Named Entity Recognition, Prompt Engineering, Pyspark, Python, Regular expressions, SQL, Supervised ML, Tokenization, Transformer Models, Transformers, Unstructured Data Pre-processing, and Unsupervised ML. Tredence, founded in 2013, is a company dedicated to transforming data into actionable insights. With a focus on helping over 50 Fortune 500 clients succeed in their industries, we operate globally with our headquarters in San Jose and a presence in 5 countries. Our goal is to be the world's most indispensable analytics partner by combining deep domain expertise with advanced AI and data science to deliver exceptional business value. We welcome you to be a part of our team and contribute to our innovative journey.,