ML Engineer

Carsome’s Data Department is on the lookout for a Data Scientist/Senior Data Scientist who has a strong passion in building data powered products.

 

Data Science function under the Data Department has a responsibility for standardisation of methods, mentoring team of data science resources/interns, including code libraries and documentation, quality assurance of outputs, modeling techniques and statistics, leveraging a variety of technologies, open-source languages, and cloud computing platform. 

 

You will get to lead & implement projects such as price optimization/prediction, enabling iconic personalization experiences for our customer, inventory optimization etc.

 

Job Descriptions

 

• Identifying and integrating datasets that can be leveraged through our product and work closely with data engineering team to develop data products.
• Execute analytical experiments methodically to help solve various problems and make a true impact across functions such as operations, finance, logistics, marketing. 
• Identify, prioritize, and design testing opportunities that will inform algorithm enhancements. 
• Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy.
• Unlock insights by analyzing large amounts of complex website traffic and transactional data. 
• Implement analytical models into production by collaborating with data analytics engineers.

 

Technical Requirements

 

• Expertise in model design, training, evaluation, and implementation ML Algorithm expertise K-nearest neighbors, Random Forests, Naive Bayes, Regression Models. PyTorch, TensorFlow, Keras, deep learning expertise, tSNE, gradient boosting expertise, regression implementation expertise, Python, Pyspark, SQL, R, AWS Sagemaker /personalize etc.
• Machine Learning / Data Science Certification

 

Experience & Education 

 

• Bachelor’s in Engineering / Master’s in Data Science  / Postgraduate Certificate in Data Science. 

Job Title -Data Scientist

 

Job Duties

1. Data Scientist responsibilities includes planning projects and building analytics models.
2. You should have a strong problem-solving ability and a knack for statistical analysis.
3. If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.

 

Responsibilities

Own end-to-end business problems and metrics, build and implement ML solutions using cutting-edge technology.

Create scalable solutions to business problems using statistical techniques, machine learning, and NLP.

Design, experiment and evaluate highly innovative models for predictive learning

Work closely with software engineering teams to drive real-time model experiments, implementations, and new feature creations

Establish scalable, efficient, and automated processes for large-scale data analysis, model development, deployment, experimentation, and evaluation.

Research and implement novel machine learning and statistical approaches.

 

Requirements

 

2-5 years of experience in data science.

In-depth understanding of modern machine learning techniques and their mathematical underpinnings.

Demonstrated ability to build PoCs for complex, ambiguous problems and scale them up.

Strong programming skills (Python, Java)

High proficiency in at least one of the following broad areas: machine learning, statistical modelling/inference, information retrieval, data mining, NLP

Experience with SQL and NoSQL databases

Strong organizational and leadership skills

Excellent communication skills

Responsibilities:

 

• Designing and implementing fine-tuned production ready data/ML pipelines in Hadoop platform.
• Driving optimization, testing and tooling to improve quality.
• Reviewing and approving high level & amp; detailed design to ensure that the solution delivers to the business needs and aligns to the data & analytics architecture principles and roadmap.
• Understanding business requirements and solution design to develop and implement solutions that adhere to big data architectural guidelines and address business requirements.
• Following proper SDLC (Code review, sprint process).
• Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, etc.
• Building robust and scalable data infrastructure (both batch processing and real-time) to support needs from internal and external users.
• Understanding various data security standards and using secure data security tools to apply and adhere to the required data controls for user access in the Hadoop platform.
• Supporting and contributing to development guidelines and standards for data ingestion.
• Working with a data scientist and business analytics team to assist in data ingestion and data related technical issues.
• Designing and documenting the development & deployment flow.

 

Requirements:

 

• Experience in developing rest API services using one of the Scala frameworks.
• Ability to troubleshoot and optimize complex queries on the Spark platform
• Expert in building and optimizing ‘big data’ data/ML pipelines, architectures and data sets.
• Knowledge in modelling unstructured to structured data design.
• Experience in Big Data access and storage techniques.
• Experience in doing cost estimation based on the design and development.
• Excellent debugging skills for the technical stack mentioned above which even includes analyzing server logs and application logs.
• Highly organized, self-motivated, proactive, and ability to propose best design solutions.
• Good time management and multitasking skills to work to deadlines by working independently and as a part of a team.

 

Profile (must have skills and experience) we are looking for
● Statistics - Always makes data-driven decisions using tools from statistics, such as: populations and
sampling, normal distribution and central limit theorem, mean, median, mode, variance, standard
deviation, covariance, correlation, p-value, expected value, conditional probability and Bayes's theorem
● Machine Learning
○ Solid grasp of attention mechanism, transformers, convolutions, optimisers, loss functions,
LSTMs, forget gates, activation functions.
○ Can implement all of these from scratch in pytorch, tensorflow or numpy.
○ Comfortable defining own model architectures, custom layers and loss functions.
● Modelling
○ Comfortable with using all the major ML frameworks (pytorch, tensorflow, sklearn, etc) and NLP
models (not essential). Able to pick the right library and framework for the job.
○ Capable of turning research and papers into operational execution and functionality delivery.

About Us :

Docsumo is Document AI software that helps enterprises capture data and analyze customer documents. We convert documents such as invoices, ID cards, and bank statements into actionable data. We are work with clients such as PayU, Arbor and Hitachi and backed by Sequoia, Barclays, Techstars, and Better Capital.

 

As a Senior Machine Learning you will be working directly with the CTO to develop end to end API products for the US market in the information extraction domain.

 

Responsibilities :

• You will be designing and building systems that help Docsumo process visual data i.e. as PDF & images of documents.
• You'll work in our Machine Intelligence team, a close-knit group of scientists and engineers who incubate new capabilities from whiteboard sketches all the way to finished apps.
• You will get to learn the ins and outs of building core capabilities & API products that can scale globally.
• Should have hands-on experience applying advanced statistical learning techniques to different types of data.
• Should be able to design, build and work with RESTful Web Services in JSON and XML formats. (Flask preferred)
• Should follow Agile principles and processes including (but not limited to) standup meetings, sprints and retrospectives.

Skills / Requirements :

• Minimum 3+ years experience working in machine learning, text processing, data science, information retrieval, deep learning, natural language processing, text mining, regression, classification, etc.
• Must have a full-time degree in Computer Science or similar (Statistics/Mathematics)
• Working with OpenCV, TensorFlow and Keras
• Working with Python: Numpy, Scikit-learn, Matplotlib, Panda
• Familiarity with Version Control tools such as Git
• Theoretical and practical knowledge of SQL / NoSQL databases with hands-on experience in at least one database system.
• Must be self-motivated, flexible, collaborative, with an eagerness to learn

• Perform research and development on Machine Learning specifically in the areas of Speech Recognition, Digital signal processing, audio signal processing, NaturalLanguage processing, Natural Language Understanding
• Read and keep up with the research in Speech recognition, Machine Learning, Deep

           Learning

• Understand and implement research papers to the business problem and build the

           technology

• Contribute to applied research and open source community
• Mentor and guide team members

• Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
• Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”. 
• Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models. 
• Partner with data scientists to understand and implement machine learning algorithms. 
• Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models. 
• Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders. 
• Mentor junior team members 

 

Who we have in mind:

• Graduate in Computer Science or related field, or equivalent practical experience. 
• 4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
• Proficiency with SQL,  Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
• Familiarity with deep learning frameworks such as TensorFlow or Keras
• Experience with Computer Vision (OpenCV),  NLP frameworks (NLTK, SpaCY, BERT).
• Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering). 
• Understand machine learning principles (training, validation, etc.) 
• Strong hands-on knowledge of data query and data processing tools (i.e. SQL) 
• Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code. 
• Experience deploying highly scalable software supporting millions or more users 
• Experience building applications on cloud  (AWS or Azure) 
• Experience working in scrum teams with Agile tools like JIRA
• Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users

 

 

 

 

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.

Job Summary DataToBiz is an AI and Data Analytics Services startup. We are a team of young and dynamic professionals looking for an exceptional data scientist to join our team in Chandigarh. We are trying to solve some very exciting business challenges by applying cutting-edge Machine Learning and Deep Learning Technology. Being a consulting and services startup we are looking for quick learners who can work in a cross-functional team of Consultants, SMEs from various domains, UX architects, and Application development experts, to deliver compelling solutions through the application of Data Science and Machine Learning. The desired candidate will have a passion for finding patterns in large datasets, an ability to quickly understand the underlying domain and expertise to apply Machine Learning tools and techniques to create insights from the data. Responsibilities and Duties As a Data Scientist on our team, you will be responsible for solving complex big-data problems for various clients (on-site and off-site) using data mining, statistical analysis, machine learning, deep learning. One of the primary responsibilities will be to understand the business need and translate it into an actionable analytical plan in consultation with the team. Ensure that the analytical plan aligns with the customer’s overall strategic need. Understand and identify appropriate data sources required for solving the business problem at hand. Explore, diagnose and resolve any data discrepancies – including but not limited to any ETL that may be required, missing value and extreme value/outlier treatment using appropriate methods. Execute project plan to meet requirements and timelines. Identify success metrics and monitor them to ensure high-quality output for the client. Deliver production-ready models that can be deployed in the production system. Create relevant output documents, as required – power point deck/ excel files, data frames etc. Overall project management - Creating a project plan and timelines for the project and obtain sign-off. Monitor project progress in conjunction with the project plan – report risks, scope creep etc. in a timely manner. Identify and evangelize new and upcoming analytical trends in the market within the organization. Implementing the applications of these algorithms/methods/techniques in R/Python Required Experience, Skills and Qualifications 3+ years experience working Data Mining and Statistical Modeling for predictive and prescriptive enterprise analytics. 2+ years of working with Python, Machine learning with exposure to one or more ML/DL frameworks like Tensorflow, Caffe, Scikit-Learn, MXNet, CNTK. Exposure to ML techniques and algorithms to work with different data formats including Structured Data, Unstructured Data, and Natural Language. Experience working with data retrieval and manipulation tools for various data sources like: Rest/Soap APIs, Relational (MySQL) and No-SQL Databases (MongoDB), IOT data streams, Cloud-based storage, and HDFS. Strong foundation in Algorithms and Data Science theory. Strong verbal and written communication skills with other developers and business client Knowledge of Telecom and/or FinTech Domain is a plus.

JOB DESCRIPTION We're looking for Head, Machine learning (3+ years experience) for our company - Spotmentor Technologies. Right now our Technology team has 5 members and this is a head team member role and carries significant equity with it. We need someone who can lead the Machine learning function with both vision and hands-on work and is excited to use this area to develop B2B products for enterprise productivity. RESPONSIBILITIES • Collaborate with cross-functional team members to develop software libraries, tools, and methodologies as critical components of our computation platforms. • Also responsible for software profiling, performance tuning and analysis, and other general software engineering tasks. • Use independent judgment to take existing code, understand its function, and change/enhance as needed. • Work as a team leader rather than a member. REQUIREMENTS • Proficient in Python with sound knowledge in the machine learning libraries namely Scikit-learn, Numpy, Pandas, NLTK etc. • Experience with Deep Learning tools like TensorFlow, Keras, PyTorch etc and integrating using open source learning platforms is required. • Prior experience in building a fully functional Machine Learning Algorithm in the text analysis and multi-class classification with promising results. • Expert data scientist with professionalism in text classification, text analytics, regression and other machine learning algorithms. • Solid grasp of mathematical principles behind machine learning algorithms. • Proficient in using version control tools (Git, Mercurial etc). • Prior experience of using big data technologies like Hadoop, Spark etc. • Semantic Web experience is a big plus. • Should be from tier 1 colleges (IIT’s / NIT’s and BITS).