We are looking for a Data Scientist 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.
- Identify valuable data sources and automate collection processes
- Undertake preprocessing of structured and unstructured data
- Analyze large amounts of information to discover trends and patterns
- Build predictive models and machine-learning algorithms
- Combine models through ensemble modeling
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Collaborate with engineering and product development teams
- Proven experience as a Data Scientist or Data Analyst
- Experience in data mining
- Understanding of machine-learning and operations research
- Knowledge of SQL,Python,R,ggplot2, matplotlib, seaborn, Shiny, Dash; familiarity with Scala, Java or C++ is an asset
- Experience using business intelligence tools (e.g. Tableau) and data frameworks
- Analytical mind and business acumen
- Strong math skills in statistics, algebra
- Problem-solving aptitude
- Excellent communication and presentation skills
- BSc/BE in Computer Science, Engineering or relevant field;
- graduate degree in Data Science or other quantitative field is preferred
Subodh PopalwarSoftware Engineer, Memorres
About TechUnity Software Systems India Pvt Ltd;
What You’ll Do:
In-depth and strong knowledge of SQL.
- Basic knowledge of Java.
- Basic scripting knowledge.
- Strong analytical skills.
- Excellent debugging skills and problem-solving.
Who You Are:
- Comfortable working in EST+IST Timezone.
- Troubleshoot complex issues discovered in-house as well as in customer environments.
- Replicate customer environments/issues on Platform and Data and work to identify the root cause or provide interim workaround as needed.
- Ability to debug SQL queries associated with Data pipelines.
- Monitoring and debugging ETL job on a daily basis.
- Provide Technical Action plans to take a customer/product issue from start to resolution.
- Capture and document any Data incidents identified on Platform and maintain the history for such issues along with resolution.
- Identify product bugs and improvements based on customer environments and work to close them
- Ensure implementation/continuous improvement of formal processes to support product development activities.
- Good in external and internal communication across stakeholders.
Your key responsibilities
- Create and maintain optimal data pipeline architecture. Should have experience in building batch/real-time ETL Data Pipelines. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
- The individual will be responsible for solution design, integration, data sourcing, transformation, database design and implementation of complex data warehousing solutions.
- Responsible for development, support, maintenance, and implementation of a complex project module
- Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint
- Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation
- Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support.
- complete reporting solutions.
- Preparation of HLD about architecture of the application and high level design.
- Preparation of LLD about job design, job description and in detail information of the jobs.
- Preparation of Unit Test cases and execution of the same.
- Provide technical guidance and mentoring to application development teams throughout all the phases of the software development life cycle
Skills and attributes for success
- Strong experience in SQL. Proficient in writing performant SQL working with large data volumes. Proficiency in writing and debugging complex SQLs.
- Strong experience in database system Microsoft Azure. Experienced in Azure Data Factory.
- Strong in Data Warehousing concepts. Experience with large-scale data warehousing architecture and data modelling.
- Should have enough experience to work on Power Shell Scripting
- Able to guide the team through the development, testing and implementation stages and review the completed work effectively
- Able to make quick decisions and solve technical problems to provide an efficient environment for project implementation
- Primary owner of delivery, timelines. Review code was written by other engineers.
- Maintain highest levels of development practices including technical design, solution development, systems configuration, test documentation/execution, issue identification and resolution, writing clean, modular and self-sustaining code, with repeatable quality and predictability
- Must have understanding of business intelligence development in the IT industry
- Outstanding written and verbal communication skills
- Should be adept in SDLC process - requirement analysis, time estimation, design, development, testing and maintenance
- Hands-on experience in installing, configuring, operating, and monitoring CI/CD pipeline tools
- Should be able to orchestrate and automate pipeline
- Good to have : Knowledge of distributed systems such as Hadoop, Hive, Spark
To qualify for the role, you must have
- Bachelor's Degree in Computer Science, Economics, Engineering, IT, Mathematics, or related field preferred
- More than 6 years of experience in ETL development projects
- Proven experience in delivering effective technical ETL strategies
- Microsoft Azure project experience
- Technologies: ETL- ADF, SQL, Azure components (must-have), Python (nice to have)
Ideally, you’ll also have
About our Client :-
Our Client is a global data and measurement-driven media agency whose mission is to make brands more valuable to the world. Clients include Google, Flipkart, NBCUniversal, L'Oréal and the Financial Times. The agency is more than 2,000 people strong, manages $4.5B in annualized media spend, and deploys campaigns in 121 markets via 22 offices in APAC, EMEA and the Americas.
About the role :-
Accountable for quantifying and measuring the success of our paid media campaigns and for delivering insights that enable us to innovate the work we deliver at MFG. Leading multi-product projects, developing best practices, being the main point of contact for other teams and direct line management for multiple team members.
Some of the things we’d like you to do -
● Build a deep understanding of marketing plans and their objectives to help Account teams (Activation, Planning, etc) build comprehensive measurement, and test & learn plans
● Play an instrumental role in evolving and designing new, innovative measurement tools. Managing the process through to delivery and take ownership of global roll out
● Recruit, manage and mentor analytical resource(s), ensuring the efficient flow of work through the team, the timely delivery of high-quality outputs and their continuing development as professionals
● Lead the creation of clear, robust and thought-provoking campaign reviews and insights
● Work with Account teams (Activation, Planning, etc) to help define the correct questions to understand correct metrics for quantifying campaign performance
● To help deliver “best in class” analytical capabilities across the agency with the wider Analytics team, including the use of new methods, techniques, tools and systems
● Develop innovative marketing campaigns and assist clients to define objectives
● Develop deep understanding of marketing platform testing and targeting abilities, and act in a consultative capacity in their implementation
● Provide hands-on leadership, mentorship, and coaching in the expert delivery of data strategies, AdTech solutions, audiences solutions and data management solutions to our clients
● Leading stakeholder management on certain areas of the client portfolio
● Coordination and communication with 3rd party vendors to critically assess new/bespoke measurement solutions. Includes development and management of contracts and SOWs.
A bit about yourself -
● 8+ years of experience in a data & insight role; practical experience on how analytical techniques/models are used in marketing. Previous agency, media, or consultancy background is desirable.
● A proven track record in working with a diverse array of clients to solve complex problems and delivering demonstrable business success. Including (but not limited to) the development of compelling and sophisticated data strategies and AdTech / martech strategies to enable
● Ideally you have worked with Ad Platforms, DMPs, CDPs, Clean Rooms, Measurement Platforms, Business Intelligence Tools, Data Warehousing and Big Data Solutions to some degree
● 3+ years of management experience and ability to delegate effectively
● Proficiency with systems such as SQL, Social Analytics tools, Python, and ‘R’
● Understand measurement for both Direct Response and Brand Awareness campaigns desired
● Excellent at building and presenting data in a visually engaging and insightful manner that cuts through the noise
● Strong organizational and project management skills including team resourcing
● Strong understanding of what data points can be collected and analyzed in a digital campaign, and how each data point should be analyzed
● Established and professional communication, presentation, and motivational skills
The company is World's No1 Global management consulting firm.
Graduate or post graduate degree in statistics, economics, econometrics, computer science,
engineering, or mathematics
2-5 years of relevant experience
Adept in forecasting, regression analysis and segmentation work
Understanding of modeling techniques, specifically logistic regression, linear regression, cluster
analysis, CHAID, etc.
Statistical programming software experience in R & Python, comfortable working with large data
sets; SAS & SQL are also preferred
Excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify
root causes and recommend solutions
Excellent time management skills
Good written and verbal communication skills; understanding of both written and spoken English
Strong interpersonal skills
Ability to act autonomously, bringing structure and organization to work
Creative and action-oriented mindset
Ability to interact in a fluid, demanding and unstructured environment where priorities evolve
constantly and methodologies are regularly challenged
Ability to work under pressure and deliver on tight deadlines
Function: Product → Product Analytics
- Assist product managers in the formulation of the company's product strategy using structured data and insights derived from the same
- Conduct research, create business cases and translate them into meaningful problems to solve
- Measure impact of experiments related to function, analysing and helping in course correction.
- Recommending product improvements based on analytical findings. Defining new metrics, techniques, and strategies to improve performance.
- Constantly monitor and analyse metrics identified, publish insights/any anomalies along with hypothesis
- Translating business requirements and user requests into effective report and dashboard designs in challenging deadlines.
- Assist with performance tuning of dashboards, background data queries as needed
Key Skills Required:
- Bachelor’s degree along with 2+ years experience in product analytics building data sets, reports, and dashboards
- Strong analytics skills and experience in Metabase, Google Analytics, Power BI, or other analytics software
- Proficiency with SQL
- Agile ability to anticipate need, be responsive and adapt to change
- Strong interpersonal and relationship skills, ability to influence decisions and gain consensus
- Excellent time and project management skills, ability to prioritise the most important projects to create business impact
Perks at Oneistox:
- Challenging work, High Product Ownership, and Steep Learning Curve are guaranteed!
- You get to be part of a highly young and energetic team.
- Envisage the growth of a company from 5X to 500X.
- Industry standard compensation and ESOPS.
Roles and Responsibilities
- Managing available resources such as hardware, data, and personnel so that deadlines are met.
- Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
- Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Defining validation framework and establish a process to ensure acceptable data quality criteria are met
- Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
- Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
- Device self-learning strategies through analysis of errors from the models
- Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
- Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
- Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.
Preferred Technical & Professional expertise
- Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
- At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
- In-depth knowledge of cloud analytics tools.
- Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
- Ability to evaluate hardware selection for running ML models for optimal performance
- Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
- Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
- Deep analytical thinking with excellent problem-solving abilities
- Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
- Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
- Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
- Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards
- Adept at Machine learning techniques and algorithms.
Feature selection, dimensionality reduction, building and
- optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Doing ad-hoc analysis and presenting results
- Proficiency in using query languages such as N1QL, SQL
Experience with data visualization tools, such as D3.js, GGplot,
- Plotly, PyPlot, etc.
Creating automated anomaly detection systems and constant tracking
- of its performance
- Strong in Python is a must.
- Strong in Data Analysis and mining is a must
- Deep Learning, Neural Network, CNN, Image Processing (Must)
Building analytic systems - data collection, cleansing and
Experience with NoSQL databases, such as Couchbase, MongoDB,
- Creating, designing and developing data models
- Prepare plans for all ETL (Extract/Transformation/Load) procedures and architectures
- Validating results and creating business reports
- Monitoring and tuning data loads and queries
- Develop and prepare a schedule for a new data warehouse
- Analyze large databases and recommend appropriate optimization for the same
- Administer all requirements and design various functional specifications for data
- Provide support to the Software Development Life cycle
- Prepare various code designs and ensure efficient implementation of the same
- Evaluate all codes and ensure the quality of all project deliverables
- Monitor data warehouse work and provide subject matter expertise
- Hands-on BI practices, data structures, data modeling, SQL skills
- Minimum 1 year experience in Pyspark
- Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
- Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
- Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
- Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
- Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
- Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree and Random forest Algorithms.
- PolyBase queries for exporting and importing data into Azure Data Lake.
- Building data models both tabular and multidimensional using SQL Server data tools.
- Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
- Programming experience using python libraries NumPy, Pandas and Matplotlib.
- Implementing NOSQL databases and writing queries using cypher.
- Designing end user visualizations using Power BI, QlikView and Tableau.
- Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
- Experience using the expression languages MDX and DAX.
- Experience in migrating on-premise SQL server database to Microsoft Azure.
- Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
- Performance tuning complex SQL queries, hands on experience using SQL Extended events.
- Data modeling using Power BI for Adhoc reporting.
- Raw data load automation using T-SQL and SSIS
- Expert in migrating existing on-premise database to SQL Azure.
- Experience in using U-SQL for Azure Data Lake Analytics.
- Hands on experience in generating SSRS reports using MDX.
- Experience in designing predictive models using Python and SQL Server.
- Developing machine learning models using Azure Databricks and SQL Server
• Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc.
• Experience in selecting features, building and optimizing classifiers using machine learning techniques.
• Prior experience with data visualization tools, such as D3.js, GGplot, etc..
• Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc..
• Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders.
• Basic understanding of the banking industry is value add
Develop, process, cleanse and enhance data collection procedures from multiple data sources.
• Conduct & deliver experiments and proof of concepts to validate business ideas and potential value.
• Test, troubleshoot and enhance the developed models in a distributed environments to improve it's accuracy.
• Work closely with product teams to implement algorithms with Python and/or R.
• Design and implement scalable predictive models, classifiers leveraging machine learning, data regression.
• Facilitate integration with enterprise applications using APIs to enrich implementations