Improving statistics on a large "WHERE IN" SQL Server query
The issue may not be with improving statistics, but rather a problematic indexing strategy. 

Indexing all (or many) columns is usually not effective. Indexes were intended to be built from a small number of high-cardinality columns using small data types (int, bigints, small varchars). 

You may consider hashing any huge columns like the varbinary(max) as part of the insert or ETL process and then indexing them: 

How to handle uniqueness of many large columns in SQL Server?

How many rows in your main table? What percent of those rows will be returned by your query?

I ask because if your query returns ~20% of the data then nonclustered indexes will probably be eliminated as a retrieval path because scanning NC indexes can result in hitting the same datapage at different times during the scan to retrieve multiple rows on that page.