Python
Machine Learning (ML)Most companies try to meet expectations, dunnhumby exists to defy them. Using big data, deep expertise and AI-driven platforms to decode the 21st century human experience – then redefine it in meaningful and surprising ways that put customers first. Across digital, mobile and retail. For brands like Tesco, Coca-Cola, Procter & Gamble and PepsiCo.
We’re looking for an Applied Data Scientist who expects more from their career. It’s a chance to apply your expertise to distil complex problems into compelling insights using the best of machine learning and human creativity to deliver effective and impactful solutions for clients. Joining our advanced data science team, you’ll investigate, develop, implement and deploy a range of complex applications and components while working alongside super-smart colleagues challenging and rewriting the rules, not just following them.
What we expect from you
- Degree in Statistics, Maths, Physics, Economics or similar field
- Programming skills (Python and SQL are a must have)
- Analytical Techniques and Technology
- Experience with and passion for connecting your work directly to the customer experience, making a real and tangible impact.
- Logical thinking and problem solving
- Strong communication skills
- Statistical Modelling and experience of applying data science into client problems
- 2 to 5 years of experience required
What you can expect from us
We won’t just meet your expectations. We’ll defy them. So you’ll enjoy the comprehensive rewards package you’d expect from a leading technology company. But also, a degree of personal flexibility you might not.
Plus, thoughtful perks, like early finish Friday and your birthday off.
You’ll also benefit from an investment in cutting-edge technology that reflects our global ambition. But with a nimble, small-business feel that gives you the freedom to play, experiment and learn.
And we don’t just talk about diversity and inclusion. We live it every day – with thriving networks including dh Women’s Network, dh Proud, dh Parent’s & Carer’s, dh One and dh Thrive as the living proof. Everyone’s invited.
Our approach to Flexible Working
At dunnhumby, we value and respect difference and are committed to building an inclusive culture by creating an environment where you can balance a successful career with your commitments and interests outside of work.
We believe that you will do your best at work if you have a work / life balance. Some roles lend themselves to flexible options more than others, so if this is important to you please raise this with your recruiter, as we are open to discussing agile working opportunities during the hiring process.
Subodh Popalwar
Software Engineer, Memorres
About DUNNHUMBY IT SERVICES INDIA
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• Demonstrated experience in leading programs.
• Prior experience in customer data platforms/finance domain is a plus.
• Demonstrated ability in developing and deploying data-driven products.
• Experience of working with large datasets and developing scalable algorithms.
• Hands-on experience of working with tech, product, and operation teams.
Technical Skills:
• Deep understanding and hands-on experience of Machine learning and Deep
learning algorithms. Good understanding of NLP and LLM concepts and fair
experience in developing NLU and NLG solutions.
• Experience with Keras/TensorFlow/PyTorch deep learning frameworks.
• Proficient in scripting languages (Python/Shell), SQL.
• Good knowledge of Statistics.
• Experience with big data, cloud, and MLOps.
Soft Skills:
• Strong analytical and problem-solving skills.
• Excellent presentation and communication skills.
• Ability to work independently and deal with ambiguity.
Continuous Learning:
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Qualification.
A degree in Computer Science, Statistics, Applied Mathematics, Machine Learning, or any related field / B. Tech.
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BE/Btect/ME/MTech
PythonRole: Principal Software Engineer
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• Software Development that creates data driven intelligence in the products which deals with Big Data backends
• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements
• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development
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• Creating metrics and evaluation of algorithm for better accuracy and recall
• Ensuring efficient access and usage of data through the means of indexing, clustering etc.
• Collaborate with engineering and product development teams.
Requirements:
• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school
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• Experience of 8 to 10 year with product development, having done algorithmic work
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• In depth Knowledge Python programming languages
• Understanding of software architecture and software design
• Must have fully managed a project with a team
• Having worked with Agile project management practices
• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)
• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis
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- 2+ years of experience (4+ for Senior Data Engineer) with system/data integration, development or implementation of enterprise and/or cloud software Engineering degree in Computer Science, Engineering or related field.
- Extensive hands-on experience with data integration/EAI technologies (File, API, Queues, Streams), ETL Tools and building custom data pipelines.
- Demonstrated proficiency with Python, JavaScript and/or Java
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- Experience with relational and NoSQL databases (any vendor) Solid understanding of cloud computing concepts.
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Data SciencePythonAbout the Company
Blue Sky Analytics is a Climate Tech startup that combines the power of AI & Satellite data to aid in the creation of a global environmental data stack. Our funders include Beenext and Rainmatter. Over the next 12 months, we aim to expand to 10 environmental data-sets spanning water, land, heat, and more!
We are looking for a data scientist to join its growing team. This position will require you to think and act on the geospatial architecture and data needs (specifically geospatial data) of the company. This position is strategic and will also require you to collaborate closely with data engineers, data scientists, software developers and even colleagues from other business functions. Come save the planet with us!
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Develop: You will be required to develop processes and tools to monitor and analyze data and its accuracy. You will develop innovative algorithms which will be useful in tracking global environmental problems like depleting water levels, illegal tree logging, and even tracking of oil-spills.
Demonstrate: A familiarity with working in geospatial libraries such as GDAL/Rasterio for reading/writing of data, and use of QGIS in making visualizations. This will also extend to using advanced statistical techniques and applying concepts like regression, properties of distribution, and conduct other statistical tests.
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- Flexible timings: Fit your work around your lifestyle.
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- Quarterly Retreats: Yes there's work-but then there's all the non-work+fun aspect aka the retreat!
- Yearly vacations: Take time off to rest and get ready for the next big assignment by availing the paid leaves.
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Development of data platforms, integration frameworks, processes, and code.
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Elaborate stories in a collaborative agile environment (SCRUM or Kanban)
Familiarity with cloud platforms like GCP, AWS or Azure.
Experience with large data volumes.
Familiarity with writing rest-based services.
Experience with distributed processing and systems
Experience with Hadoop / Spark toolsets
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Data Science
R ProgrammingPython1) 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.
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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.
Data ScienceR ProgrammingPython
Data Analytics- Identifying valuable data sources and automate collection processes
- Undertaking preprocessing of structured and unstructured data
- Analyzing large amounts of information to discover trends and patterns
- Building predictive models and machine-learning algorithms
- Combining models through ensemble modeling
- Presenting information using data visualization techniques
- Proposing solutions and strategies to business challenges
- Collaborating with engineering and product development teams
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- Data Scientist with min 3 years of experience in Analytics or Data Science preferably in Pricing or Polymer Market
- Experience using scripting languages like Python(preferred) or R is a must.
- Experience with SQL, Tableau is good to have
- Strong numerical, problem solving and analytical aptitude
- Being able to make data based decisions
- Ability to present/communicate analytics driven insights.
- Critical and Analytical thinking skills
Responsibilities for Data Engineer
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Python
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Software Engineer, Memorres