Target is an iconic brand, a Fortune 50 company and one of America’s leading retailers. Behind one of the world’s best-loved brands is a uniquely capable and brilliant team of data scientists, engineers and analysts. The Target Data Science & Analytics team creates the tools and data products to sustainably educate and enable our business partners to make great data-based decisions. We help develop the technology that personalizes the guest experience, from product recommendations to relevant ad content. We are also the source of the data and analytics behind Target’s Internet of Things (IOT) applications, fraud detection, Supply Chain optimization and demand forecasting. We play a key role in identifying the test-and-measure or A/B test opportunities that continuously help Target improve the guest experience, whether they love to shop in stores or at Target.com. A role with Data Science and Analytics (DSA) means being a part of the team that works closely with the business and identifies problems / opportunities for improved decision-making through better data analysis. This covers the whole gamut from simple descriptive analysis to more complex predictive and prescriptive analytics, using advanced modeling and machine learning techniques primarily using open source technologies and big data platforms. The emphasis is on actionable insights, which is possible through a combination of technical skills and business understanding. As Data Analyst, DSA you will work closely with business/product teams and understand their priorities/roadmap. Based on this understanding, you are expected to identify appropriate metrics that will drive the right decisions for the business, and then build reporting solutions to deliver these metrics at the required frequency in an optimal and reliable fashion. You will also answer ad-hoc questions from your business users by conducting quick analysis on relevant data, identify trends and correlations, and form hypotheses to explain the observations. Some of these will lead to bigger analytical projects of increasing complexity, where you will work initially as a part of a bigger team, but also work independently as you gain more experience. Finally, you are expected to always adhere to project schedule and technical rigor as well as requirements for documentation, code versioning, etc. Core responsibilities are described within this job description. Job duties may change at any time due to business needs. About You: B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent 1+ years of relevant experience “Hands-on” experience in analytics / data science Understanding of foundational mathematics and statistics Conceptual understanding of analytical techniques like Linear Regression, Logistic Regression, Time-series models, Classification Techniques, etc. Basic SQL skills Strong written and verbal communication skills to explain complex analytical methodologies to clients regardless of the clients technical expertise Exposure to R, Python, Hive, or other open source languages preferable Big data experience preferable
The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain. At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain. Candidates will be expected to lead projects across several areas such as Demand forecasting Inventory management Simulation & Mathematical optimization models. Procurement analytics Distribution/Logistics planning Network planning and optimization Qualification and Experience 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain. Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain Hands-on experience in delivery of projects using statistical modelling Skills / Knowledge Hands on experience in statistical modelling software such as R/ Python and SQL. Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage. Highly proficient with Excel, PowerPoint and Word applications. APICS-CSCP or PMP certification will be added advantage Strong knowledge of supply chain management Working knowledge on the linear/nonlinear optimization Ability to structure problems through a data driven decision-making process. Excellent project management skills, including time and risk management and project structuring. Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis. Ability to liaison effectively with multiple stakeholders and functional disciplines. Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.
About us DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.Data Science@DataWeaveWe the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.How we work?It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!What do we offer?- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!- Ability to see the impact of your work and the value you're adding to our customers almost immediately.- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.- Last but not the least, competitive salary packages and fast paced growth opportunities.Who are we looking for?The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities. We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred). Key problem areas- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.- Ensemble approaches for all the above problems using multiple text and image based techniques.Relevant set of skills- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.- Use the command line like a pro. Be proficient in Git and other essential software development tools.- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.Role and responsibilities- Understand the business problems we are solving. Build data science capability that align with our product strategy.- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.- Build robust clustering and classification models in an iterative manner that can be used in production.- Constantly think scale, think automation. Measure everything. Optimize proactively.- Take end to end ownership of the projects you are working on. Work with minimal supervision.- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.