Data Scientist

Minimum of 8 years of experience of which, 4 years should be of applied data mining

experience in disciplines such as Call Centre Metrics.

 Strong experience in advanced statistics and analytics including segmentation, modelling, regression, forecasting etc.

 Experience with leading and managing large teams.

 Demonstrated pattern of success in using advanced quantitative analytic methods to solve business problems.

 Demonstrated experience with Business Intelligence/Data Mining tools to work with

data, investigate anomalies, construct data sets, and build models.

 Critical to share details on projects undertaken (preferably on telecom industry)

specifically through analysis from CRM.

Role : Sr Data Scientist / Tech Lead – Data Science

Number of positions : 8

Responsibilities

• Lead a team of data scientists, machine learning engineers and big data specialists
• Be the main point of contact for the customers
• Lead data mining and collection procedures
• Ensure data quality and integrity
• Interpret and analyze data problems
• Conceive, plan and prioritize data projects
• Build analytic systems and predictive models
• Test performance of data-driven products
• Visualize data and create reports
• Experiment with new models and techniques
• Align data projects with organizational goals

Requirements (please read carefully)

• Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
• Msc-Statistics/ Phd.Statistics
• Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
• Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
• Proven experience as a Data Scientist or similar role, for about 7-8 years
• Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
• Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
• Knowledge of data management and visualization techniques --- more from a Data Science perspective.
• Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
• Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.

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Job Title: Data Engineer

Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.

Responsibilities:

• Design, build, and maintain data pipelines to collect, store, and process data from various sources.
• Create and manage data warehousing and data lake solutions.
• Develop and maintain data processing and data integration tools.
• Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
• Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
• Ensure data quality and integrity across all data sources.
• Develop and implement best practices for data governance, security, and privacy.
• Monitor data pipeline performance / Errors and troubleshoot issues as needed.
• Stay up-to-date with emerging data technologies and best practices.

Requirements:

Bachelor's degree in Computer Science, Information Systems, or a related field.

Experience with ETL tools like Matillion,SSIS,Informatica

Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.

Experience in writing complex SQL queries

Strong programming skills in languages such as Python, Java, or Scala.

Experience with data modeling, data warehousing, and data integration.

Strong problem-solving skills and ability to work independently.

Excellent communication and collaboration skills.

Familiarity with big data technologies such as Hadoop, Spark, or Kafka.

Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks

Familiarity with cloud computing platforms such as AWS, Azure, or GCP.

Familiarity with Reporting tools

Teamwork/ growth contribution

• Helping the team in taking the Interviews and identifying right candidates
• Adhering to timelines
• Intime status communication and upfront communication of any risks
• Tech, train, share knowledge with peers.
• Good Communication skills
• Proven abilities to take initiative and be innovative
• Analytical mind with a problem-solving aptitude

Good to have :

Master's degree in Computer Science, Information Systems, or a related field.

Experience with NoSQL databases such as MongoDB or Cassandra.

Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.

Knowledge of machine learning and statistical modeling techniques.

If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.

Senior Data Scientist-Job Description

The Senior Data Scientist role is a creative problem solver who utilizes statistical/mathematical principles and modelling skills to uncover new insights that will significantly and meaningfully impact business decisions and actions.  She/he applies their data science expertise in identifying, defining, and executing state-of-art techniques for academic opportunities and business objectives in collaboration with other Analytics team members. The Senior Data Scientist will execute analyses & outputs spanning test design and measurement, predictive analytics, multivariate analysis, data/text mining, pattern recognition, artificial intelligence, and machine learning.

Key Responsibilities:

• Perform the full range of data science activities including test design and measurement, predictive/advanced analytics, and data mining, and analytic dashboards.
• Extract, manipulate, analyse & interpret data from various corporate data sources developing advanced analytic solutions, deriving key observations, findings, insights, and formulating actionable recommendations.
• Generate clearly understood and intuitive data science / advanced analytics outputs.
• Provide thought leadership and recommendations on business process improvement, analytic solutions to complex problems.
• Participate in best practice sharing and communication platform for advancement of the data science discipline.
• Coach and collaborate with other data scientists and data analysts.
• Present impact, insights, outcomes & recommendations to key business partners and stakeholders.
• Comply with established Service Level Agreements to ensure timely, high quality deliverables with value-add recommendations, clearly articulated key findings and observations.

Qualification:

• Bachelor's Degree (B.A./B.S.) or Master’s Degree (M.A./M.S.) in Computer Science, Statistics, Mathematics, Machine Learning, Physics, or similar degree
• 5+ years of experience in data science in a digitally advanced industry focusing on strategic initiatives, marketing and/or operations.
• Advanced knowledge of best-in-class analytic software tools and languages: Python, SQL, R, SAS, Tableau, Excel, PowerPoint.
• Expertise in statistical methods, statistical analysis, data visualization, and data mining techniques.
• Experience in Test design, Design of Experiments, A/B Testing, Measurement Science Strong influencing skills to drive a robust testing agenda and data driven decision making for process improvements
• Strong Critical thinking skills to track down complex data and engineering issues, evaluate different algorithmic approaches, and analyse data to solve problems.
• Experience in partnering with IT, marketing operations & business operations to deploy predictive analytic solutions.
• Ability to translate/communicate complex analytical/statistical/mathematical concepts with non-technical audience.
• Strong written and verbal communications skills, as well as presentation skills.

• Research and develop statistical learning models for data analysis
• Collaborate with product management and engineering departments to understand company needs and devise possible solutions
• Keep up-to-date with latest technology trends
• Communicate results and ideas to key decision makers
• Implement new statistical or other mathematical methodologies as needed for specific models or analysis
• Optimize joint development efforts through appropriate database use and project design

Qualifications/Requirements:

• Masters or PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
• Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc
• 3+ years experiences building data science-driven solutions including data collection, feature selection, model training, post-deployment validation
• Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning models
• Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
• Good team worker with excellent communication skills written, verbal and presentation

Desired Experience:

• Experience with AWS, S3, Flink, Spark, Kafka, Elastic Search
• Knowledge and experience with NLP technology
• Previous work in a start-up environment

• Design, create, test, and maintain data pipeline architecture in collaboration with the Data Architect.
• Build the infrastructure required for extraction, transformation, and loading of data from a wide variety of data sources using Java, SQL, and Big Data technologies.
• Support the translation of data needs into technical system requirements. Support in building complex queries required by the product teams.
• Build data pipelines that clean, transform, and aggregate data from disparate sources
• Develop, maintain and optimize ETLs to increase data accuracy, data stability, data availability, and pipeline performance.
• Engage with Product Management and Business to deploy and monitor products/services on cloud platforms.
• Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale with the increased data sets of consumer experience.
• Handle data integration, consolidation, and reconciliation activities for digital consumer / medical products.

Job Qualifications:

• Bachelor’s or master's degree in Computer Science, Information management, Statistics or related field
• 5+ years of experience in the Consumer or Healthcare industry in an analytical role with a focus on building on data pipelines, querying data, analyzing, and clearly presenting analyses to members of the data science team.
• Technical expertise with data models, data mining.
• Hands-on Knowledge of programming languages in Java, Python, R, and Scala.
• Strong knowledge in Big data tools like the snowflake, AWS Redshift, Hadoop, map-reduce, etc.
• Having knowledge in tools like AWS Glue, S3, AWS EMR, Streaming data pipelines, Kafka/Kinesis is desirable.
• Hands-on knowledge in SQL and No-SQL database design.
• Having knowledge in CI/CD for the building and hosting of the solutions.
• Having AWS certification is an added advantage.
• Having Strong knowledge in visualization tools like Tableau, QlikView is an added advantage
• A team player capable of working and integrating across cross-functional teams for implementing project requirements. Experience in technical requirements gathering and documentation.
• Ability to work effectively and independently in a fast-paced agile environment with tight deadlines
• A flexible, pragmatic, and collaborative team player with the innate ability to engage with data architects, analysts, and scientists

About the Company:

 It is a Data as a Service company that helps businesses harness the power of data. Our technology fuels some of the most interesting big data projects of the word. We are a small bunch of people working towards shaping the imminent data-driven future by solving some of its fundamental and toughest challenges. 

Role: We are looking for an experienced team lead to drive data acquisition projects end to end. In this role, you will be working in the web scraping team with data engineers, helping them solve complex web problems and mentor them along the way. You’ll be adept at delivering large-scale web crawling projects, breaking down barriers for your team and planning at a higher level, and getting into the detail to make things happen when needed.  

Responsibilities  

•  Interface with clients and sales team to translate functional requirements into technical requirements 
•  Plan and estimate tasks with your team, in collaboration with the delivery managers 
•  Engineer complex data acquisition projects 
•  Guide and mentor your team of engineers 
•  Anticipate issues that might arise and proactively consider those into design 
•  Perform code reviews and suggest design changes 

Prerequisites 

•  Between 5-8 years of relevant experience 
• Fluent programming skills and well-versed with scripting languages like Python or Ruby 
• Solid foundation in data structures and algorithms 
• Excellent tech troubleshooting skills 
• Good understanding of web data landscape 
• Prior exposure to DOM, XPATH and hands on experience with selenium/automated testing is a plus 

Skills and competencies 

• Prior experience with team handling and people management is mandatory 
• Work independently with little to no supervision 
• Extremely high attention to detail  
•  Ability to juggle between multiple projects