Data Analytics Trainer

Responsible for developing and maintaining applications with PySpark 

Job description

• The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Roles & Responsibilities

• Experience using statistical languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Experience working with and creating data architectures.
• Looking for someone with 3-7 years of experience manipulating data sets and building statistical models
• Has a Bachelor's, Master's in Computer Science or another quantitative field
• Knowledge and experience in statistical and data mining techniques :
• GLM/Regression, Random Forest, Boosting, Trees, text mining,social network analysis, etc.
• Experience querying databases and using statistical computer languages :R, Python, SQL, etc.
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees,neural networks, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.

• Proficiency in shell scripting
• Proficiency in automation of tasks
• Proficiency in Pyspark/Python
• Proficiency in writing and understanding of sqoop
• Understanding of CloudEra manager
• Good understanding of RDBMS
• Good understanding of Excel

 

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.

Associate Director – Data Science

Tiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.
We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.

About the Role:

As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.
• Work closely with internal teams and client stakeholders to design analytical approaches to
solve business problems
• Develop and enhance a broad range of cutting-edge data analytics and machine learning
problems across a variety of industries.
• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &
versioning, documentation, scaling, deployment, monitoring and maintenance etc.
• Lead a team of data scientists and engineers to embed AI and analytics into the client
business decision processes.

Desired Skills:

• High level of proficiency in a structured programming language, e.g. Python, R.
• Experience designing data science solutions to business problems
• Deep understanding of ML algorithms for common use cases in both structured and
unstructured data ecosystems.
• Comfortable with large scale data processing and distributed computing
• Excellent written and verbal communication skills
• 10+ years exp of which 8 years of relevant data science experience including hands-on
programming.

Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.

• Core Java: advanced level competency, should have worked on projects with core Java development.

 

• Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands

 

• Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.

 

• Data structures and problem solving: should have ability to use appropriate data structure.

 

• AWS cloud : Good to have experience with aws serverless toolset along with aws infra

 

• Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)

 

• Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets

 

• HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.

 

• Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.

 

WyngCommerce is building state of the art AI software for the Global Consumer Brands & Retailers to enable best-in-class customer experiences. Our vision is to democratize machine learning algorithms for our customers and help them realize dramatic improvements in speed, cost and flexibility. Backed by a clutch of prominent angel investors & having some of the category leaders in the retail industry as clients, we are looking to hire for our data science team. The data science team at WyngCommerce is on a mission to challenge the norms and re-imagine how retail business should be run across the world. As a Junior Data Scientist in the team, you will be driving and owning the thought leadership and impact on one of our core data science problems. You will work collaboratively with the founders, clients and engineering team to formulate complex problems, run Exploratory Data Analysis and test hypotheses, implement ML-based solutions and fine tune them with more data. This is a high impact role with goals that directly impact our business. Your Role & Responsibilities: - Implement data-driven solutions based on advanced ML and optimization algorithms to address business problems - Research, experiment, and innovate ML/statistical approaches in various application areas of interest and contribute to IP - Partner with engineering teams to build scalable, efficient, automated ML-based pipelines (training/evaluation/monitoring) - Deploy, maintain, and debug ML/decision models in production environment - Analyze and assess data to ensure high data quality and correctness of downstream processes - Communicate results to stakeholders and present data/insights to participate in and drive decision making Desired Skills & Experiences: - Bachelors or Masters in a quantitative field from a top tier college - 1-2 years experience in a data science / analytics role in a technology / analytics company - Solid mathematical background (especially in linear algebra & probability theory) - Familiarity with theoretical aspects of common ML techniques (generalized linear models, ensembles, SVMs, clustering algos, graphical models, etc.), statistical tests/metrics, experiment design, and evaluation methodologies - Demonstrable track record of dealing with ambiguity, prioritizing needs, bias for iterative learning, and delivering results in a dynamic environment with minimal guidance - Hands-on experience in at least one of the following: (a) Anomaly Detection, (b) Time Series Analysis, (c) Product Clustering, (d) Demand Forecasting, (e) Intertemporal Optimization - Good programming skills (fluent in Java/Python/SQL) with experience of using common ML toolkits (e.g., sklearn, tensor flow, keras, nltk) to build models for real world problems - Computational thinking and familiarity with practical application requirements (e.g., latency, memory, processing time) - Excellent written and verbal communication skills for both technical and non-technical audiences - (Plus Point) Experience of applying ML / other techniques in the domain of supply chain - and particularly in retail - for inventory optimization, demand forecasting, assortment planning, and other such problems - (Nice to have) Research experience and publications in top ML/Data science conferences