Data Engineer

• 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

Role & Responsibilities:
1) Understand the business objectives, formulate hypotheses and collect the relevant data using SQL/R/Python. Analyse bureau, customer and lending performance data on a periodic basis to generate insights. Present complex information and data in an uncomplicated, easyto-understand way to drive action.
2) Independently Build and refit robust models for achieving game-changing growth while managing risk.
3) Identify and implement new analytical/modelling techniques to improve model performance across customer lifecycle (acquisitions, management, fraud, collections, etc.
4) Help define the data infrastructure strategy for Indian subsidiary.
a. Monitor data quality and quantity.
b. Define a strategy for acquisition, storage, retention, and retrieval of data elements. e.g.: Identify new data types and collaborate with technology teams to capture them.
c. Build a culture of strong automation and monitoring
d. Staying connected to the Analytics industry trends - data, techniques, technology, etc. and leveraging them to continuously evolve data science standards at Credit Saison.

Required Skills & Qualifications:
1) 3+ years working in data science domains with experience in building risk models. Fintech/Financial analysis experience is required.
2) Expert level proficiency in Analytical tools and languages such as SQL, Python, R/SAS, VBA etc.
3) Experience with building models using common modelling techniques (Logistic and linear regressions, decision trees, etc.)
4) Strong familiarity with Tableau//Power BI/Qlik Sense or other data visualization tools
5) Tier 1 college graduate (IIT/IIM/NIT/BITs preferred).
6) Demonstrated autonomy, thought leadership, and learning agility.

SQL Developer with Relevant experience of 7 Yrs with Strong Communication Skills.

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identify, design, and implement internal process improvements
4. Optimize data delivery and re-design infrastructure for greater scalability
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
7. Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs
8. Create data tools for analytics and data scientist team members
 
Skills Required:
 
1. Working knowledge of ETL on any cloud (Azure / AWS / GCP)
2. Proficient in Python (Programming / Scripting)
3. Good understanding of any of the data warehousing concepts (Snowflake / AWS Redshift / Azure Synapse Analytics / Google Big Query / Hive)
4. In-depth understanding of principles of database structure
5.  Good understanding of any of the ETL technologies (Informatica PowerCenter / AWS Glue / Data Factory / SSIS / Spark / Matillion / Talend / Azure)
6. Proficient in SQL (query solving)
7. Knowledge in Change case Management / Version Control – (VSS / DevOps / TFS / GitHub, Bit bucket, CICD Jenkin)

Simplilearn.com is the world’s largest professional certifications company and an Onalytica Top 20 influential brand. With a library of 400+ courses, we've helped 500,000+ professionals advance their careers, delivering $5 billion in pay raises. Simplilearn has over 6500 employees worldwide and our customers include Fortune 1000 companies, top universities, leading agencies and hundreds of thousands of working professionals. We are growing over 200% year on year and having fun doing it. Description We are looking for candidates with strong technical skills and proven track record in building predictive solutions for enterprises. This is a very challenging role and provides an opportunity to work on developing insights based Ed-Tech software products used by large set of customers across globe. It provides an exciting opportunity to work across various advanced analytics & data science problem statement using cutting-edge modern technologies collaborating with product, marketing & sales teams. Responsibilities • Work on enterprise level advanced reporting requirements & data analysis. • Solve various data science problems customer engagement, dynamic pricing, lead scoring, NPS improvement, optimization, chatbots etc. • Work on data engineering problems utilizing our tech stack - S3 Datalake, Spark, Redshift, Presto, Druid, Airflow etc. • Collect relevant data from source systems/Use crawling and parsing infrastructure to put together data sets. • Craft, conduct and analyse A/B experiments to evaluate machine learning models/algorithms. • Communicate findings and take algorithms/models to production with ownership. Desired Skills • BE/BTech/MSc/MS in Computer Science or related technical field. • 2-5 years of experience in advanced analytics discipline with solid data engineering & visualization skills. • Strong SQL skills and BI skills using Tableau & ability to perform various complex analytics in data. • Ability to propose hypothesis and design experiments in the context of specific problems using statistics & ML algorithms. • Good overlap with Modern Data processing framework such as AWS-lambda, Spark using Scala or Python. • Dedication and diligence in understanding the application domain, collecting/cleaning data and conducting various A/B experiments. • Bachelor Degree in Statistics or, prior experience with Ed-Tech is a plus

We are actively seeking a Senior Data Engineer experienced in building data pipelines and integrations from 3rd party data sources by writing custom automated ETL jobs using Python. The role will work in partnership with other members of the Business Analytics team to support the development and implementation of new and existing data warehouse solutions for our clients. This includes designing database import/export processes used to generate client data warehouse deliverables.

 

Indium Software is a niche technology solutions company with deep expertise in Digital , QA and Gaming. Indium helps customers in their Digital Transformation journey through a gamut of solutions that enhance business value.

With over 1000+ associates globally, Indium operates through offices in the US, UK and India

Visit www.indiumsoftware.com to know more.

Job Title: Analytics Data Engineer

What will you do:
The Data Engineer must be an expert in SQL development further providing support to the Data and Analytics in database design, data flow and analysis activities. The position of the Data Engineer also plays a key role in the development and deployment of innovative big data platforms for advanced analytics and data processing. The Data Engineer defines and builds the data pipelines that will enable faster, better, data-informed decision-making within the business.

We ask:

Extensive Experience with SQL and strong ability to process and analyse complex data

The candidate should also have an ability to design, build, and maintain the business’s ETL pipeline and data warehouse The candidate will also demonstrate expertise in data modelling and query performance tuning on SQL Server
Proficiency with analytics experience, especially funnel analysis, and have worked on analytical tools like Mixpanel, Amplitude, Thoughtspot, Google Analytics, and similar tools.

Should work on tools and frameworks required for building efficient and scalable data pipelines
Excellent at communicating and articulating ideas and an ability to influence others as well as drive towards a better solution continuously.
Experience working in python, Hive queries, spark, pysaprk, sparkSQL, presto

• Relate Metrics to product
• Programmatic Thinking
• Edge cases
• Good Communication
• Product functionality understanding

Perks & Benefits:
A dynamic, creative & intelligent team they will make you love being at work.
Autonomous and hands-on role to make an impact you will be joining at an exciting time of growth!

Flexible work hours and Attractive pay package and perks
An inclusive work environment that lets you work in the way that works best for you!

Understanding business objectives and developing models that help to achieve them,
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
Exploring and visualizing 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
Verifying data quality, and/or ensuring it via data cleaning
Supervising the data acquisition process if more data is needed
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production

Job Description : Role : Analytics Scientist - Risk Analytics Experience Range : 1 to 4 Years Job Location : Noida Key responsibilities include •Building models to predict risk and other key metrics •Coming up with data driven solutions to control risk •Finding opportunities to acquire more customers by modifying/optimizing existing rules •Doing periodic upgrades of the underwriting strategy based on business requirements •Evaluating 3rd party solutions for predicting/controlling risk of the portfolio •Running periodic controlled tests to optimize underwriting •Monitoring key portfolio metrics and take data driven actions based on the performance Business Knowledge: Develop an understanding of the domain/function. Manage business process (es) in the work area. The individual is expected to develop domain expertise in his/her work area. Teamwork: Develop cross site relationships to enhance leverage of ideas. Set and manage partner expectations. Drive implementation of projects with Engineering team while partnering seamlessly with cross site team members Communication: Responsibly perform end to end project communication across the various levels in the organization. Candidate Specification: Skills: • Knowledge of analytical tool - R Language or Python • Established competency in Predictive Analytics (Logistic & Regression) • Experience in handling complex data sources •Dexterity with MySQL, MS Excel is good to have •Strong Analytical aptitude and logical reasoning ability •Strong presentation and communication skills Preferred: •1 - 3 years of experience in Financial Services/Analytics Industry •Understanding of the financial services business • Experience in working on advanced machine learning techniques If interested, please send your updated profile in word format with below details for further discussion at the earliest. 1. Current Company 2. Current Designation 3. Total Experience 4. Current CTC( Fixed & Variable) 5. Expected CTC 6. Notice Period 7. Current Location 8. Reason for Change 9. Availability for face to face interview on weekdays 10.Education Degreef the financial services business Thanks & Regards, Hema Talent Socio