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- Data pre-processing, data transformation, data analysis, and feature engineering
- Performance optimization of scripts (code) and Productionizing of code (SQL, Pandas, Python or PySpark, etc.)
- Required skills:
- Bachelors in - in Computer Science, Data Science, Computer Engineering, IT or equivalent
- Fluency in Python (Pandas), PySpark, SQL, or similar
- Azure data factory experience (min 12 months)
- Able to write efficient code using traditional, OO concepts, modular programming following the SDLC process.
- Experience in production optimization and end-to-end performance tracing (technical root cause analysis)
- Ability to work independently with demonstrated experience in project or program management
- Azure experience ability to translate data scientist code in Python and make it efficient (production) for cloud deployment
LogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.
Responsibilities :
Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties
Requirements:
Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.
Data Scientist – Program Embedded
Job Description:
We are seeking a highly skilled and motivated senior data scientist to support a big data program. The successful candidate will play a pivotal role in supporting multiple projects in this program covering traditional tasks from revenue management, demand forecasting, improving customer experience to testing/using new tools/platforms such as Copilot Fabric for different purpose. The expected candidate would have deep expertise in machine learning methodology and applications. And he/she should have completed multiple large scale data science projects (full cycle from ideation to BAU). Beyond technical expertise, problem solving in complex set-up will be key to the success for this role. This is a data science role directly embedded into the program/projects, stake holder management and collaborations with patterner are crucial to the success on this role (on top of the deep expertise).
What we are looking for:
- Highly efficient in Python/Pyspark/R.
- Understand MLOps concepts, working experience in product industrialization (from Data Science point of view). Experience in building product for live deployment, and continuous development and continuous integration.
- Familiar with cloud platforms such as Azure, GCP, and the data management systems on such platform. Familiar with Databricks and product deployment on Databricks.
- Experience in ML projects involving techniques: Regression, Time Series, Clustering, Classification, Dimension Reduction, Anomaly detection with traditional ML approaches and DL approaches.
- Solid background in statistics, probability distributions, A/B testing validation, univariate/multivariate analysis, hypothesis test for different purpose, data augmentation etc.
- Familiar with designing testing framework for different modelling practice/projects based on business needs.
- Exposure to Gen AI tools and enthusiastic about experimenting and have new ideas on what can be done.
- If they have improved an internal company process using an AI tool, that would be great (e.g. process simplification, manual task automation, auto emails)
- Ideally, 10+ years of experience, and have been on independent business facing roles.
- CPG or retail as a data scientist would be nice, but not number one priority, especially for those who have navigated through multiple industries.
- Being proactive and collaborative would be essential.
Some projects examples within the program:
- Test new tools/platforms such as Copilo, Fabric for commercial reporting. Testing, validation and build trust.
- Building algorithms for predicting trend in category, consumptions to support dashboards.
- Revenue Growth Management, create/understand the algorithms behind the tools (can be built by 3rd parties) we need to maintain or choose to improve. Able to prioritize and build product roadmap. Able to design new solutions and articulate/quantify the limitation of the solutions.
- Demand forecasting, create localized forecasts to improve in store availability. Proper model monitoring for early detection of potential issues in the forecast focusing particularly on improving the end user experience.
About Us:
We are a VC-funded startup solving one of the biggest transportation problems India faces. Most passengers in India travel long distance by IRCTC trains. At time of booking, approx 1 out of every 2 passengers end up with a Waitlisted or RAC ticket. This creates a lot of anxiety for passengers, as Railway only announces only 4 hour before departure if they have a confirmed seat. We solve this problem through our Waitlist & RAC Protection. Protection can be bought against each IRCTC ticket at time of booking. If train ticket is not confirmed, we fly the passenger to the destination. Our team consists of 3 Founders from IIT, IIM and ISB.
Functional Experience:
- Computer Science or IT Engineering background with solid understanding of basics of Data Structures and Algorithms
- 2+ years of data science experience working with large datasets
- Expertise in Python packages like pandas, numPy, sklearn, matplotlib, seaborn, keras and tensorflow
- Expertise in Big Data technologies like Hadoop, Cassandra and PostgreSQL
- Expertise in Cloud computing on AWS with EC2, AutoML, Lambda and RDS
- Good knowledge of Machine Learning and Statistical time series analysis (optional)
- Unparalleled logical ability making you the go to guy for all things related to data
- You love coding like a hobby and are up for a challenge!
Cultural:
- Assume a strong sense of ownership of analytics : Design, develop & deploy
- Collaborate with senior management, operations & business team
- Ensure Quality & sustainability of the architecture
- Motivation to join an early stage startup should go beyond compensation
at Virtusa
- Minimum 1 years of relevant experience, in PySpark (mandatory)
- Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus
- Ability to play lead role and independently manage 3-5 member of Pyspark development team
- EMR ,Python and PYspark mandate.
- Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS
- Hands-on experience in any Cloud Platform
- Microsoft Azure Experience
They provide both wholesale and retail funding. PM1
- Key responsibility is to design and develop a data pipeline including the architecture, prototyping, and development of data extraction, transformation/processing, cleansing/standardizing, and loading in Data Warehouse at real-time/near the real-time frequency. Source data can be structured, semi-structured, and/or unstructured format.
- Provide technical expertise to design efficient data ingestion solutions to consolidate data from RDBMS, APIs, Messaging queues, weblogs, images, audios, documents, etc of Enterprise Applications, SAAS applications, external 3rd party sites or APIs, etc through ETL/ELT, API integrations, Change Data Capture, Robotic Process Automation, Custom Python/Java Coding, etc
- Development of complex data transformation using Talend (BigData edition), Python/Java transformation in Talend, SQL/Python/Java UDXs, AWS S3, etc to load in OLAP Data Warehouse in Structured/Semi-structured form
- Development of data model and creating transformation logic to populate models for faster data consumption with simple SQL.
- Implementing automated Audit & Quality assurance checks in Data Pipeline
- Document & maintain data lineage to enable data governance
- Coordination with BIU, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc
Requirements
- Programming experience using Python / Java, to create functions / UDX
- Extensive technical experience with SQL on RDBMS (Oracle/MySQL/Postgresql etc) including code optimization techniques
- Strong ETL/ELT skillset using Talend BigData Edition. Experience in Talend CDC & MDM functionality will be an advantage.
- Experience & expertise in implementing complex data pipelines, including semi-structured & unstructured data processing
- Expertise to design efficient data ingestion solutions to consolidate data from RDBMS, APIs, Messaging queues, weblogs, images, audios, documents, etc of Enterprise Applications, SAAS applications, external 3rd party sites or APIs, etc through ETL/ELT, API integrations, Change Data Capture, Robotic Process Automation, Custom Python/Java Coding, etc
- Good understanding & working experience in OLAP Data Warehousing solutions (Redshift, Synapse, Snowflake, Teradata, Vertica, etc) and cloud-native Data Lake (S3, ADLS, BigQuery, etc) solutions
- Familiarity with AWS tool stack for Storage & Processing. Able to recommend the right tools/solutions available to address a technical problem
- Good knowledge of database performance and tuning, troubleshooting, query optimization, and tuning
- Good analytical skills with the ability to synthesize data to design and deliver meaningful information
- Good knowledge of Design, Development & Performance tuning of 3NF/Flat/Hybrid Data Model
- Know-how on any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc) will be an advantage.
- Ability to understand business functionality, processes, and flows
- Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently
Functional knowledge
- Data Governance & Quality Assurance
- Distributed computing
- Linux
- Data structures and algorithm
- Unstructured Data Processing
● Ability to do exploratory analysis: Fetch data from systems and analyze trends.
● Developing customer segmentation models to improve the efficiency of marketing and product
campaigns.
● Establishing mechanisms for cross functional teams to consume customer insights to improve
engagement along the customer life cycle.
● Gather requirements for dashboards from business, marketing and operations stakeholders.
● Preparing internal reports for executive leadership and supporting their decision making.
● Analyse data, derive insights and embed it into Business actions.
● Work with cross functional teams.
Skills Required
• Data Analytics Visionary.
• Strong in SQL & Excel and good to have experience in Tableau.
• Experience in the field of Data Analysis, Data Visualization.
• Strong in analysing the Data and creating dashboards.
• Strong in communication, presentation and business intelligence.
• Multi-Dimensional, "Growth Hacker" Skill Set with strong sense of ownership for work.
• Aggressive “Take no prisoners” approach.
Nactus is at forefront of education reinvention, helping educators and learner’s community at large through innovative solutions in digital era. We are looking for an experienced AI specialist to join our revolution using the deep learning, artificial intelligence. This is an excellent opportunity to take advantage of emerging trends and technologies to a real-world difference.
Role and Responsibilities
- Manage and direct research and development (R&D) and processes to meet the needs of our AI strategy.
- Understand company and client challenges and how integrating AI capabilities can help create educational solutions.
- Analyse and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards.
Skills Required
- Knowledge of algorithms, object-oriented and functional design principles
- Demonstrated artificial intelligence, machine learning, mathematical and statistical modelling knowledge and skills.
- Well-developed programming skills – specifically in SAS or SQL and other packages with statistical and machine learning application, e.g. R, Python
- Experience with machine learning fundamentals, parallel computing and distributed systems fundamentals, or data structure fundamentals
- Experience with C, C++, or Python programming
- Experience with debugging and building AI applications.
- Robustness and productivity analyse conclusions.
- Develop a human-machine speech interface.
- Verify, evaluate, and demonstrate implemented work.
- Proven experience with ML, deep learning, Tensorflow, Python
We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.
This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.
You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.
What you will achieve:
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Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap
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Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs
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Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists
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Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space
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Partner with the executive team and other business leaders to deliver cross-functional research work and models
Required Skills:
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Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience
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Knowledge of deep learning & NLP
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Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.
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Experience with GPU computing is a plus.
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Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.
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Expert-level experience with a wide range of quantitative methods that can be applied to business problems.
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Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.
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Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.
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Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
Qualifications
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Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization
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Expert-level experience with machine learning that can be applied to business problems
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Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization
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Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling
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Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)
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5+ years of industry experience in data science and machine learning, preferably at a software product company
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3+ years of experience managing data science teams, incl. managing/grooming managers beneath you
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3+ years of experience partnering with executive staff on data topics